{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.7.10","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"markdown","source":"# Importing Libraries","metadata":{}},{"cell_type":"code","source":"! pip install biosppy   ","metadata":{"execution":{"iopub.status.busy":"2021-09-08T18:29:16.466425Z","iopub.execute_input":"2021-09-08T18:29:16.466845Z","iopub.status.idle":"2021-09-08T18:29:27.705182Z","shell.execute_reply.started":"2021-09-08T18:29:16.466758Z","shell.execute_reply":"2021-09-08T18:29:27.704132Z"},"trusted":true},"execution_count":1,"outputs":[{"name":"stdout","text":"Collecting biosppy\n  Downloading biosppy-0.7.3.tar.gz (85 kB)\n\u001b[K     |████████████████████████████████| 85 kB 1.5 MB/s eta 0:00:011\n\u001b[?25hCollecting bidict\n  Downloading bidict-0.21.3-py3-none-any.whl (36 kB)\nRequirement already satisfied: h5py in /opt/conda/lib/python3.7/site-packages (from biosppy) (2.10.0)\nRequirement already satisfied: matplotlib in /opt/conda/lib/python3.7/site-packages (from biosppy) (3.4.2)\nRequirement already satisfied: numpy in /opt/conda/lib/python3.7/site-packages (from biosppy) (1.19.5)\nRequirement already satisfied: scikit-learn in /opt/conda/lib/python3.7/site-packages (from biosppy) (0.23.2)\nRequirement already satisfied: scipy in /opt/conda/lib/python3.7/site-packages (from biosppy) (1.6.3)\nRequirement already satisfied: shortuuid in /opt/conda/lib/python3.7/site-packages (from biosppy) (1.0.1)\nRequirement already satisfied: six in /opt/conda/lib/python3.7/site-packages (from biosppy) (1.15.0)\nRequirement already satisfied: joblib in /opt/conda/lib/python3.7/site-packages (from biosppy) (1.0.1)\nRequirement already satisfied: opencv-python in /opt/conda/lib/python3.7/site-packages (from biosppy) (4.5.2.54)\nRequirement already satisfied: pyparsing>=2.2.1 in /opt/conda/lib/python3.7/site-packages (from matplotlib->biosppy) (2.4.7)\nRequirement already satisfied: pillow>=6.2.0 in /opt/conda/lib/python3.7/site-packages (from matplotlib->biosppy) (8.2.0)\nRequirement already satisfied: kiwisolver>=1.0.1 in /opt/conda/lib/python3.7/site-packages (from matplotlib->biosppy) (1.3.1)\nRequirement already satisfied: python-dateutil>=2.7 in /opt/conda/lib/python3.7/site-packages (from matplotlib->biosppy) (2.8.1)\nRequirement already satisfied: cycler>=0.10 in /opt/conda/lib/python3.7/site-packages (from matplotlib->biosppy) (0.10.0)\nRequirement already satisfied: threadpoolctl>=2.0.0 in /opt/conda/lib/python3.7/site-packages (from scikit-learn->biosppy) (2.1.0)\nBuilding wheels for collected packages: biosppy\n  Building wheel for biosppy (setup.py) ... \u001b[?25ldone\n\u001b[?25h  Created wheel for biosppy: filename=biosppy-0.7.3-py2.py3-none-any.whl size=95409 sha256=cf13a2e640dad03ecc380a26b4a9c948e26c0e29d920d95a2a31a7ffe79a35bc\n  Stored in directory: /root/.cache/pip/wheels/2f/4f/8f/28b2adc462d7e37245507324f4817ce1c64ef2464f099f4f0b\nSuccessfully built biosppy\nInstalling collected packages: bidict, biosppy\nSuccessfully installed bidict-0.21.3 biosppy-0.7.3\n\u001b[33mWARNING: Running pip as root will break packages and permissions. You should install packages reliably by using venv: https://pip.pypa.io/warnings/venv\u001b[0m\n","output_type":"stream"}]},{"cell_type":"code","source":"import numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport tensorflow as tf\nimport wfdb\nimport os                                                                                                  \nimport gc\nimport scipy       \nimport sklearn\nfrom pathlib import Path\nfrom sklearn.utils import shuffle\nfrom sklearn.manifold import TSNE\nimport seaborn as sns\nfrom sklearn import preprocessing\nimport shutil\nimport math\nimport random\nfrom scipy.spatial import distance\nfrom biosppy.signals import ecg\nfrom scipy.interpolate import PchipInterpolator","metadata":{"execution":{"iopub.status.busy":"2021-09-08T18:29:27.706977Z","iopub.execute_input":"2021-09-08T18:29:27.707263Z","iopub.status.idle":"2021-09-08T18:29:35.032189Z","shell.execute_reply.started":"2021-09-08T18:29:27.707231Z","shell.execute_reply":"2021-09-08T18:29:35.031076Z"},"trusted":true},"execution_count":2,"outputs":[]},{"cell_type":"code","source":"try:\n    tpu = tf.distribute.cluster_resolver.TPUClusterResolver()  # TPU detection\n    print('Running on TPU ', tpu.cluster_spec().as_dict()['worker'])\nexcept ValueError:\n    raise BaseException('ERROR: Not connected to a TPU runtime; please see the previous cell in this notebook for instructions!')\n\ntf.config.experimental_connect_to_cluster(tpu)\ntf.tpu.experimental.initialize_tpu_system(tpu)\ntpu_strategy = tf.distribute.experimental.TPUStrategy(tpu)","metadata":{"execution":{"iopub.status.busy":"2021-09-08T18:29:35.033731Z","iopub.execute_input":"2021-09-08T18:29:35.034080Z","iopub.status.idle":"2021-09-08T18:29:40.900958Z","shell.execute_reply.started":"2021-09-08T18:29:35.034045Z","shell.execute_reply":"2021-09-08T18:29:40.900038Z"},"trusted":true},"execution_count":3,"outputs":[{"name":"stdout","text":"Running on TPU  ['10.0.0.2:8470']\n","output_type":"stream"}]},{"cell_type":"markdown","source":"# Dataset Creation","metadata":{}},{"cell_type":"markdown","source":"## MIT-BIH Dataset","metadata":{}},{"cell_type":"code","source":"####### Dataset Creation  \n###### Reading Dataset\n\n##### Function to read a record from single dataset\ndef data_read_mit(filepath):\n    \n    \"\"\"\n    Function to read the the inputs from MIT-BIH Dataset\n    INPUTS:- \n    1)filepath: Path to the csv file\n    \n    OUTPUTS:-\n    1)Output_signal: Output 1D array signal \n    \"\"\"\n    return (np.array(pd.read_csv(filepath,index_col=0).iloc[:,[0]]))   \n    \n##### Function to Required Annotations from .txt files\ndef feature_extractor(txt_file_path):\n    \n    \"\"\"\n       Function to extract time series data \n       from a .txt file\n    \"\"\"\n    \n    #### Reading File\n    line_list = []\n\n    with open(txt_file_path, 'r') as reader:\n\n    # Read and print the entire file line by line\n        line = reader.readline()\n        while line != '':  # The EOF char is an empty string\n            #print(line, end='')\n            line_list.append(line)\n            line = reader.readline()\n    \n    #### Taking the Time Step Data\n    line_list = line_list[1:]\n    \n    #### Splitting the Collected Text Strings and Converting them into Floating type values\n    new_list = []\n\n    for item in line_list:\n        for idx,sub_item in enumerate(item.split()):\n            if(idx == 1):\n                new_list.append(int(sub_item))\n                break\n    \n    ### Returning the feature extracted list as numpy array\n    return np.array(new_list)\n\n###### Function to Segment Signals\n##### Constants\nFS = 500\nW_LEN = 256\nW_LEN_1_4 = 256 // 4\nW_LEN_3_4 = 3 * (256 // 4)\n\n##### Function\ndef segmentSignals(signal, r_peaks_annot, normalization=True, person_id= None, file_id=None):\n    \n    \"\"\"\n    Segments signals based on the detected R-Peak\n    Args:\n        signal (numpy array): input signal\n        r_peaks_annot (int []): r-peak locations.\n        normalization (bool, optional): apply z-normalization or not? . Defaults to True.\n        person_id ([type], optional): [description]. Defaults to None.\n        file_id ([type], optional): [description]. Defaults to None.\n    Returns:\n            [tuple(numpy array,numpy array)]: segmented signals and refined r-peaks\n    \"\"\"\n    def refine_rpeaks(signal, r_peaks):\n        \"\"\"\n        Refines the detected R-peaks. If the R-peak is slightly shifted, this assigns the \n        highest point R-peak.\n        Args:\n            signal (numpy array): input signal\n            r_peaks (int []): list of detected r-peaks\n        Returns:\n            [numpy array]: refined r-peaks\n        \"\"\"\n\n        r_peaks2 = np.array(r_peaks)            # make a copy\n        for i in range(len(r_peaks)):\n            r = r_peaks[i]          # current R-peak\n            small_segment = signal[max(0,r-100):min(len(signal),r+100)]         # consider the neighboring segment of R-peak\n            r_peaks2[i] = np.argmax(small_segment) - 100 + r_peaks[i]           # picking the highest point\n            r_peaks2[i] = min(r_peaks2[i],len(signal))                          # the detected R-peak shouldn't be outside the signal\n            r_peaks2[i] = max(r_peaks2[i],0)                                    # checking if it goes before zero    \n        return r_peaks2                     # returning the refined r-peak list\n    \n    segmented_signals = []                      # array containing the segmented beats\n    \n    r_peaks = np.array(r_peaks_annot)\n    r_peaks = refine_rpeaks(signal, r_peaks)\n    skip_len = 5 # Parameter to specify number of r_peaks in one signal\n    max_seq_len = 1280 # Parameter to specify maximum sequence length\n    \n    for r_curr in range(0,int(r_peaks.shape[0]-(skip_len-1)),skip_len):\n        if ((r_peaks[r_curr]-W_LEN_1_4)<0) or ((r_peaks[r_curr+(skip_len-1)]+W_LEN_3_4)>=len(signal)):           # not enough signal to segment\n            continue\n        segmented_signal = np.array(signal[r_peaks[r_curr]-W_LEN_1_4:r_peaks[r_curr+(skip_len-1)]+W_LEN_3_4])        # segmenting a heartbeat\n        segmented_signal = list(segmented_signal)\n        #print(segmented_signal.shape)\n        \n        if(len(segmented_signal) < 1280):\n            for m in range(int(1280-len(segmented_signal))): # Zero Padding\n                segmented_signal.append(0)\n        else:\n            segmented_signal = (segmented_signal[:int(max_seq_len)])\n            \n        segmented_signal = np.array(segmented_signal)\n        \n        if(segmented_signal.shape != (1280,1)):    \n            segmented_signal = np.reshape(segmented_signal,(1280,1))\n            \n        if (normalization):             # Z-score normalization\n            if abs(np.std(segmented_signal))<1e-6:          # flat line ECG, will cause zero division error\n                continue\n            segmented_signal = (segmented_signal - np.mean(segmented_signal)) / np.std(segmented_signal)            \n              \n        #if not np.isnan(segmented_signal).any():                    # checking for nan, this will never happen\n            segmented_signals.append(segmented_signal)\n\n    return segmented_signals,r_peaks           # returning the segmented signals and the refined r-peaks","metadata":{"execution":{"iopub.status.busy":"2021-08-03T03:16:06.818503Z","iopub.execute_input":"2021-08-03T03:16:06.818899Z","iopub.status.idle":"2021-08-03T03:16:06.839175Z","shell.execute_reply.started":"2021-08-03T03:16:06.818865Z","shell.execute_reply":"2021-08-03T03:16:06.838124Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"###### Looping for Reading the Entire Dataset - OpenSet Testing\n\n! mkdir './5_Beat_Ecg_MITBIH_1' # Generating major database of datasets\ncurrent_index = 1\n\nmit_dbs_path = '../input/mitbih-database'\nfor i in range(0,96,2): # Loop over all the files\n    print(i)\n    print(np.sort(os.listdir(mit_dbs_path))[i])\n    rec_file_path = os.path.join(mit_dbs_path,str(np.sort(os.listdir(mit_dbs_path))[i])) # Path Selection\n    attr_file_path = os.path.join(mit_dbs_path,str(np.sort(os.listdir(mit_dbs_path))[i+1])) # Path Selction\n    \n    signal_current = data_read_mit(rec_file_path) # Current ECG Signal\n    r_peaks_current = feature_extractor(attr_file_path) # R-peaks\n    seg_signal_current,new_r_peaks = (segmentSignals(signal_current,list(r_peaks_current))) # Segmented ECG Signals\n    #seg_signal_current = np.array(seg_signal_current)\n    #print(seg_signal_current.shape[0])\n    \n    if(i == 48):\n        current_index = current_index-1\n        current_storage_path = './5_Beat_Ecg_MITBIH_1'+'/person'+str(current_index)\n        #Path(current_storage_path).mkdir(parents=True, exist_ok=True)\n    \n        for j in range(len(seg_signal_current)):\n            file_name_current = current_storage_path+'/Extra'+str(j)\n            np.savez_compressed(file_name_current,seg_signal_current[j])\n            \n        current_index = current_index+1\n    \n    else:\n        current_storage_path = './5_Beat_Ecg_MITBIH_1'+'/person'+str(current_index)\n        Path(current_storage_path).mkdir(parents=True, exist_ok=True)\n    \n        for j in range(len(seg_signal_current)):\n            file_name_current = current_storage_path+'/'+str(j)\n            np.savez_compressed(file_name_current,seg_signal_current[j])\n            \n        current_index = current_index+1","metadata":{"execution":{"iopub.status.busy":"2021-08-03T03:16:17.439855Z","iopub.execute_input":"2021-08-03T03:16:17.440246Z","iopub.status.idle":"2021-08-03T03:21:24.358227Z","shell.execute_reply.started":"2021-08-03T03:16:17.440212Z","shell.execute_reply":"2021-08-03T03:21:24.356973Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"###### Creation of Numpy Arrays\n##### Defining Essentials\ndata_folder = './5_Beat_Ecg_MITBIH_1'\nX_train = []\nX_dev = []\ny_train = []     \ny_dev = []\n\n##### Looping Over to populate the dataset\nfor index,sub_data_folder in enumerate(np.sort(os.listdir(data_folder))):\n    sub_data_folder_path = os.path.join(data_folder,sub_data_folder)\n    \n    #if(index <= 33):\n          \n    for idx,item in enumerate(np.sort(os.listdir(sub_data_folder_path))): # Looping Over a person's folder\n        item_path = os.path.join(sub_data_folder_path,item)\n\n        #### Train on Past Test on Present (TPTP)\n        if(idx <= int(np.round(len(os.listdir(sub_data_folder_path))))):\n            X_train.append(np.load(item_path,allow_pickle=True)['arr_0'])\n            y_train.append(index+89) # Setting the Value of class label after 89 examples of ECG1D Dataset for CD_EMP\n            \n    print('Person'+' '+str(index+1)+'s data taken')\n    \n##### Creation of Numpy Arrays\nX_train_CD_train_MITBIH = np.array(X_train)\ny_train_CD_train_MITBIH = np.array(y_train)\n\n##### Testing arrays\nX_train = np.array(X_train)\ny_train = np.array(y_train)\n\nprint(np.max(y_train))\nprint(np.min(y_train))","metadata":{"execution":{"iopub.status.busy":"2021-08-03T03:32:10.308813Z","iopub.execute_input":"2021-08-03T03:32:10.309813Z","iopub.status.idle":"2021-08-03T03:33:17.417475Z","shell.execute_reply.started":"2021-08-03T03:32:10.309753Z","shell.execute_reply":"2021-08-03T03:33:17.4161Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## PTB Dataset","metadata":{}},{"cell_type":"code","source":"###### Constants\nFS = 360\nW_LEN = 256\nW_LEN_1_4 = 256 // 4\nW_LEN_3_4 = 3 * (256 // 4)\n\n###### Function to Segment Signals\n\ndef segmentSignals(signal, r_peaks_annot, normalization=True, person_id= None, file_id=None):\n    \n    \"\"\"\n    Segments signals based on the detected R-Peak\n    Args:\n        signal (numpy array): input signal\n        r_peaks_annot (int []): r-peak locations.\n        normalization (bool, optional): apply z-normalization or not? . Defaults to True.\n        person_id ([type], optional): [description]. Defaults to None.\n        file_id ([type], optional): [description]. Defaults to None.\n    Returns:\n            [tuple(numpy array,numpy array)]: segmented signals and refined r-peaks\n    \"\"\"\n    def refine_rpeaks(signal, r_peaks):\n        \"\"\"\n        Refines the detected R-peaks. If the R-peak is slightly shifted, this assigns the \n        highest point R-peak.\n        Args:\n            signal (numpy array): input signal\n            r_peaks (int []): list of detected r-peaks\n        Returns:\n            [numpy array]: refined r-peaks\n        \"\"\"\n        r_peaks2 = np.array(r_peaks)            # make a copy\n        for i in range(len(r_peaks)):\n            r = r_peaks[i]          # current R-peak\n            small_segment = signal[max(0,r-100):min(len(signal),r+100)]         # consider the neighboring segment of R-peak\n            r_peaks2[i] = np.argmax(small_segment) - 100 + r_peaks[i]           # picking the highest point\n            r_peaks2[i] = min(r_peaks2[i],len(signal))                          # the detected R-peak shouldn't be outside the signal\n            r_peaks2[i] = max(r_peaks2[i],0)                                    # checking if it goes before zero    \n        return r_peaks2                     # returning the refined r-peak list\n    \n    segmented_signals = []                      # array containing the segmented beats\n    \n    r_peaks = np.array(r_peaks_annot)\n\n    r_peaks = refine_rpeaks(signal, r_peaks)\n    skip_len = 5 # Parameter to specify number of r_peaks in one signal\n    max_seq_len = 1280 # Parameter to specify maximum sequence length\n    \n    for r_curr in range(0,int(r_peaks.shape[0]-(skip_len-1)),skip_len):\n        if ((r_peaks[r_curr]-W_LEN_1_4)<0) or ((r_peaks[r_curr+(skip_len-1)]+W_LEN_3_4)>=len(signal)):           # not enough signal to segment\n            continue\n        segmented_signal = np.array(signal[r_peaks[r_curr]-W_LEN_1_4:r_peaks[r_curr+(skip_len-1)]+W_LEN_3_4])        # segmenting a heartbeat\n        segmented_signal = list(segmented_signal)\n        #print(segmented_signal.shape)\n        \n        if(len(segmented_signal) < 1280):\n            for m in range(int(1280-len(segmented_signal))): # Zero Padding\n                segmented_signal.append(0)\n        else:\n            segmented_signal = (segmented_signal[:int(max_seq_len)])\n            \n        segmented_signal = np.array(segmented_signal)\n        \n        if(segmented_signal.shape != (1280,1)):    \n            segmented_signal = np.reshape(segmented_signal,(1280,1))\n            \n        if (normalization):             # Z-score normalization\n            if abs(np.std(segmented_signal))<1e-6:          # flat line ECG, will cause zero division error\n                continue\n            segmented_signal = (segmented_signal - np.mean(segmented_signal)) / np.std(segmented_signal)            \n              \n        #if not np.isnan(segmented_signal).any():                    # checking for nan, this will never happen\n            segmented_signals.append(segmented_signal)\n\n    return segmented_signals,r_peaks           # returning the segmented signals and the refined r-peaks\n\n###### Function to Read Records\n\ndef read_rec(rec_path):\n\n    \"\"\" \n    Function to read record and return Segmented Signals\n\n    INPUTS:-\n    1) rec_path : Path of the Record\n\n    OUTPUTS:-\n    1) seg_sigs : Final Segmented Signals\n\n    \"\"\"\n    number_of_peaks = 5 # For extracting the required number of peaks                                    \n    full_rec = (wfdb.rdrecord(rec_path)).p_signal[:,0] # Entire Record - Taking Signal from Lead-1\n\n    f = PchipInterpolator(np.arange(int(full_rec.shape[0])),full_rec) # Fitting Interpolation Function\n    num_samples = int(full_rec.shape[0]) # Total Samples in 1000Hz Signal\n    num_samples_final = int(num_samples*(360/1000))\n    x_samp = (np.arange(num_samples)*(1000/360))[:num_samples_final] # Fixing Interpolation Input Values\n    full_rec_interp = f(x_samp)  # Intepolating Values \n    \n    r_peaks_init = ecg.hamilton_segmenter(full_rec_interp,360)[0] # R-Peak Segmentation and input is the signal frequency of 500Hz in this case\n    final_peak_index = r_peaks_init[int(r_peaks_init.shape[0] - int((r_peaks_init.shape[0]%number_of_peaks)))-1]\n    r_peaks_final = r_peaks_init[:final_peak_index] # Final Number of R_Peaks\n    full_rec_final = full_rec_interp[:int(r_peaks_final[-1]+W_LEN)] # Final Sequence\n    seg_sigs, r_peaks_ref = segmentSignals(full_rec_final,list(r_peaks_final)) # Final Signal Segmentation\n\n    return seg_sigs","metadata":{"execution":{"iopub.status.busy":"2021-08-03T05:04:27.328231Z","iopub.execute_input":"2021-08-03T05:04:27.328691Z","iopub.status.idle":"2021-08-03T05:04:27.357273Z","shell.execute_reply.started":"2021-08-03T05:04:27.328651Z","shell.execute_reply":"2021-08-03T05:04:27.356035Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"###### Extracting List of the Elements with Two Sessions \ndir = '../input/ptb-dataset/ptb-diagnostic-ecg-database-1.0.0'\ntotal_index = 0\n#subjects_with_two = []\nsubjects = []\n\nfor item in np.sort(os.listdir(dir)):\n    #print('----------------------------------')\n    #print(item)\n    dir_sub = os.path.join(dir,item)\n    if(os.path.isdir(dir_sub)):\n        #ubjects.append(item)\n        #print(len(os.listdir(dir_sub))//3)\n        if(len(os.listdir(dir_sub))//3 >= 2):\n            subjects.append(item)\n            #total_index = total_index+1   \n            #print(item)\n        #    subjects_with_two.append(item)\n    #print('----------------------------------')\n\n#print(total_index)\n#print(subjects_with_two)\n\n#subjects = shuffle(subjects)[:100] # Shuffling and Taking 100 Subjects \n#print(subjects)\n\nprint(subjects)\nprint(len(subjects))","metadata":{"execution":{"iopub.status.busy":"2021-08-03T05:04:40.000604Z","iopub.execute_input":"2021-08-03T05:04:40.001005Z","iopub.status.idle":"2021-08-03T05:04:42.543974Z","shell.execute_reply.started":"2021-08-03T05:04:40.000974Z","shell.execute_reply":"2021-08-03T05:04:42.542898Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"###### Creation of Numpy Arrays \nmain_dir = '../input/ptb-dataset/ptb-diagnostic-ecg-database-1.0.0'\n\nX_train = []\nX_dev = []\ny_train = []\ny_dev = []\n\ncurrent_index = 0\n\n#for person_index,person_folder in enumerate(list(np.sort(os.listdir(main_dir)))):\n \nfor person_folder in np.sort(subjects):\n    \n    #if(current_index <= 231): # Taking 80% of the subjects for training \n    \n    person_folder_path = os.path.join(main_dir,person_folder)\n    person_folder_items = (list(np.sort(os.listdir(person_folder_path))))\n\n    for file_idx in range(0,len(person_folder_items),3):\n        file_path_list = str((os.path.join(person_folder_path,person_folder_items[file_idx])))\n        file_num = file_idx//3\n\n        rec_path = ''\n        for item_index in range(0,(len(file_path_list)-4)):\n            rec_path = rec_path+str(file_path_list[item_index])\n\n        seg_signal_current = read_rec(rec_path) # Extracting Records\n\n        # Division across Time\n        #for k in range(len(seg_signal_current)):\n\n        #    if(k <= np.round(len(seg_signal_current)*0.5)):\n        #        X_train.append(seg_signal_current[k])\n        #        y_train.append(current_index)\n\n        #    else:\n        #        X_dev.append(seg_signal_current[k])\n        #        y_dev.append(current_index)\n\n        if(file_num == 0):\n            for k in range(len(seg_signal_current)):\n                X_train.append(seg_signal_current[k])\n                y_train.append(current_index)\n                \n        if(file_num == 1):\n            for k in range(len(seg_signal_current)):\n                X_dev.append(seg_signal_current[k])\n                y_dev.append(current_index)\n\n    current_index = current_index+1\n    print('Processed for Person - '+str(current_index))\n\n##### Creation of Numpy Arrays\nprint(np.array(X_train).shape)\nprint(np.array(y_train).shape)\nprint(np.array(X_dev).shape)\nprint(np.array(y_dev).shape)\n\nprint(np.max(y_train))\nprint(np.min(y_train))\n\n##### Shuffling Arrays\nX_train,y_train = shuffle(X_train,y_train)\nX_dev,y_dev = shuffle(X_dev,y_dev)","metadata":{"execution":{"iopub.status.busy":"2021-08-03T05:04:56.480299Z","iopub.execute_input":"2021-08-03T05:04:56.480722Z","iopub.status.idle":"2021-08-03T05:06:49.003348Z","shell.execute_reply.started":"2021-08-03T05:04:56.480674Z","shell.execute_reply":"2021-08-03T05:06:49.001863Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## ECG-1D Dataset","metadata":{}},{"cell_type":"code","source":"####### Dataset Creation \n\n###### Constants\nFS = 360\nW_LEN = 256\nW_LEN_1_4 = 256 // 4\nW_LEN_3_4 = 3 * (256 // 4)\n\n###### Function to Read a Record\ndef read_rec(rec_path):\n\n    \"\"\" \n    Function to read record and return Segmented Signals\n\n    INPUTS:-\n    1) rec_path : Path of the Record\n\n    OUTPUTS:-\n    1) seg_sigs : Final Segmented Signals\n\n    \"\"\"\n    number_of_peaks = 2 # For extracting the required number of peaks                                    \n    full_rec = (wfdb.rdrecord(rec_path)).p_signal[:,1] # Entire Record\n\n    f = PchipInterpolator(np.arange(10000),full_rec) # Fitting Interpolation Function\n    x_samp = (np.arange(10000)*(500/360))[:7200] # Fixing Interpolation Input Values\n    full_rec_interp = f(x_samp)  # Intepolating Values \n    r_peaks_init = ecg.hamilton_segmenter(full_rec_interp,360)[0] # R-Peak Segmentation and input is the signal frequency of 500Hz in this case\n    final_peak_index = r_peaks_init[int(r_peaks_init.shape[0] - int((r_peaks_init.shape[0]%number_of_peaks)))-1]\n    r_peaks_final = r_peaks_init[:final_peak_index] # Final Number of R_Peaks\n    full_rec_final = full_rec_interp[:int(r_peaks_final[-1]+W_LEN)] # Final Sequence\n    seg_sigs, r_peaks_ref = segmentSignals(full_rec_final,list(r_peaks_final)) # Final Signal Segmentation\n\n    return seg_sigs # Returning the Ouput of the Signal Segmentation\n\n###### Function to Segment Signals\n\n##### Function\ndef segmentSignals(signal, r_peaks_annot, normalization=True, person_id= None, file_id=None):\n    \n    \"\"\"\n    Segments signals based on the detected R-Peak\n    Args:\n        signal (numpy array): input signal\n        r_peaks_annot (int []): r-peak locations.\n        normalization (bool, optional): apply z-normalization or not? . Defaults to True.\n        person_id ([type], optional): [description]. Defaults to None.\n        file_id ([type], optional): [description]. Defaults to None.\n    Returns:\n            [tuple(numpy array,numpy array)]: segmented signals and refined r-peaks\n    \"\"\"\n    def refine_rpeaks(signal, r_peaks):\n        \"\"\"\n        Refines the detected R-peaks. If the R-peak is slightly shifted, this assigns the \n        highest point R-peak.\n        Args:\n            signal (numpy array): input signal\n            r_peaks (int []): list of detected r-peaks\n        Returns:\n            [numpy array]: refined r-peaks\n        \"\"\"\n        r_peaks2 = np.array(r_peaks)            # make a copy\n        for i in range(len(r_peaks)):\n            r = r_peaks[i]          # current R-peak\n            small_segment = signal[max(0,r-100):min(len(signal),r+100)]         # consider the neighboring segment of R-peak\n            r_peaks2[i] = np.argmax(small_segment) - 100 + r_peaks[i]           # picking the highest point\n            r_peaks2[i] = min(r_peaks2[i],len(signal))                          # the detected R-peak shouldn't be outside the signal\n            r_peaks2[i] = max(r_peaks2[i],0)                                    # checking if it goes before zero    \n        return r_peaks2                     # returning the refined r-peak list\n    \n    segmented_signals = []                      # array containing the segmented beats\n    \n    r_peaks = np.array(r_peaks_annot)\n\n    r_peaks = refine_rpeaks(signal, r_peaks)\n    skip_len = 5 # Parameter to specify number of r_peaks in one signal\n    max_seq_len = 1280 # Parameter to specify maximum sequence length\n    \n    for r_curr in range(0,int(r_peaks.shape[0]-(skip_len-1)),skip_len):\n        if ((r_peaks[r_curr]-W_LEN_1_4)<0) or ((r_peaks[r_curr+(skip_len-1)]+W_LEN_3_4)>=len(signal)):           # not enough signal to segment\n            continue\n        segmented_signal = np.array(signal[r_peaks[r_curr]-W_LEN_1_4:r_peaks[r_curr+(skip_len-1)]+W_LEN_3_4])        # segmenting a heartbeat\n        segmented_signal = list(segmented_signal)\n        #print(segmented_signal.shape)\n        \n        if(len(segmented_signal) < 1280):\n            for m in range(int(1280-len(segmented_signal))): # Zero Padding\n                segmented_signal.append(0)\n        else:\n            segmented_signal = (segmented_signal[:int(max_seq_len)])\n            \n        segmented_signal = np.array(segmented_signal)\n        \n        if(segmented_signal.shape != (1280,1)):    \n            segmented_signal = np.reshape(segmented_signal,(1280,1))\n            \n        if (normalization):             # Z-score normalization\n            if abs(np.std(segmented_signal))<1e-6:          # flat line ECG, will cause zero division error\n                continue\n            segmented_signal = (segmented_signal - np.mean(segmented_signal)) / np.std(segmented_signal)            \n              \n        #if not np.isnan(segmented_signal).any():                    # checking for nan, this will never happen\n            segmented_signals.append(segmented_signal)\n\n    return segmented_signals,r_peaks           # returning the segmented signals and the refined r-peaks","metadata":{"execution":{"iopub.status.busy":"2021-08-03T03:13:42.564618Z","iopub.execute_input":"2021-08-03T03:13:42.564986Z","iopub.status.idle":"2021-08-03T03:13:42.588644Z","shell.execute_reply.started":"2021-08-03T03:13:42.564951Z","shell.execute_reply":"2021-08-03T03:13:42.587443Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"###### Numpy Array Creation \npath_to_dir = '../input/ecg1d/ecg-id-database-1.0.0'\ntotal_folders = 90\ncurrent_index = 0\n\nX_train = []\nX_dev = []\ny_train = []\ny_dev = []\n\n#for item in subjects_with_two:\nfor i in range(2,92):\n\n    if(i != 75):\n\n        print(i-1)\n        folder_path = os.path.join(path_to_dir,np.sort(os.listdir(path_to_dir))[i]) # Path Selection\n        #items_in_folder = int(len(folder_path)//3)\n        #current_storage_path = './5_Beat_Ecg_ECG1D'+'/person'+str(current_index)\n\n        #for j in os.listdir(item):\n\n        for j in range(2):\n\n            rec_path = folder_path+'/'+'rec'+'_'+str(j+1) # Path to Record\n            seg_signal_current = read_rec(rec_path)\n\n            if(j == 0):\n                for k in range(len(seg_signal_current)):\n                    #file_name_current = current_storage_path+'/'+str(j)+'_/'+str(k)\n                    #np.savez_compressed(file_name_current,seg_signal_current[k])\n                    X_train.append(seg_signal_current[k])\n                    y_train.append(current_index)\n\n            if(j == 1):\n                for k in range(len(seg_signal_current)):\n                    #file_name_current = current_storage_path+'/'+str(j)+'_/'+str(k)\n                    #np.savez_compressed(file_name_current,seg_signal_current[k])\n                    X_train.append(seg_signal_current[k])\n                    y_train.append(current_index)\n\n        current_index = current_index+1\n\n###### Creation of Numpy Arrays\nX_train_CD_train_ECG1D = np.array(X_train)\ny_train_CD_train_ECG1D = np.array(y_train)\n\n###### Checking Shape of the Arrays\nprint(np.array(X_train).shape)\nprint(np.array(y_train).shape)\n\nprint(np.max(y_train))\nprint(np.min(y_train))","metadata":{"execution":{"iopub.status.busy":"2021-08-03T03:14:09.107301Z","iopub.execute_input":"2021-08-03T03:14:09.107794Z","iopub.status.idle":"2021-08-03T03:14:14.388937Z","shell.execute_reply.started":"2021-08-03T03:14:09.107765Z","shell.execute_reply":"2021-08-03T03:14:14.387608Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"##### Plotting and Testing the Dataset\n\nfor i in range(100,110):\n    print(y_train[i])\n    plt.plot(np.arange(1280),X_train[i])\n    plt.show()","metadata":{"execution":{"iopub.status.busy":"2021-08-02T11:27:23.794631Z","iopub.execute_input":"2021-08-02T11:27:23.794993Z","iopub.status.idle":"2021-08-02T11:27:25.182268Z","shell.execute_reply.started":"2021-08-02T11:27:23.794959Z","shell.execute_reply":"2021-08-02T11:27:25.181158Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## Dataset Creation and Loading ","metadata":{}},{"cell_type":"markdown","source":"### Training Data","metadata":{}},{"cell_type":"code","source":"###### Amalgamating Datasets \nX_train = np.array(list(X_train_CD_train_ECG1D)+list(X_train_CD_train_MITBIH))\ny_train = np.array(list(y_train_CD_train_ECG1D)+list(y_train_CD_train_MITBIH))\n\nX_train,y_train = shuffle(X_train,y_train)\n\nprint(X_train.shape)\nprint(y_train.shape)","metadata":{"execution":{"iopub.status.busy":"2021-08-03T03:34:57.362821Z","iopub.execute_input":"2021-08-03T03:34:57.363274Z","iopub.status.idle":"2021-08-03T03:34:59.162161Z","shell.execute_reply.started":"2021-08-03T03:34:57.363237Z","shell.execute_reply":"2021-08-03T03:34:59.160951Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"###### Saving Numpy Arrays\nnp.savez_compressed('./X_train_CD_EMP.npz',np.array(X_train))\nnp.savez_compressed('./y_train_CD_EMP.npz',np.array(y_train))","metadata":{"execution":{"iopub.status.busy":"2021-08-03T03:35:05.957615Z","iopub.execute_input":"2021-08-03T03:35:05.958066Z","iopub.status.idle":"2021-08-03T03:37:16.536437Z","shell.execute_reply.started":"2021-08-03T03:35:05.958028Z","shell.execute_reply":"2021-08-03T03:37:16.534392Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"##### Loading Dataset - Training Dataset\nX_train = np.array(np.load('./X_train_CD_EMP.npz',allow_pickle=True)['arr_0'],dtype=np.float16)\ny_train = np.array(np.load('./y_train_CD_EMP.npz',allow_pickle=True)['arr_0'],dtype=np.float16)","metadata":{"execution":{"iopub.status.busy":"2021-08-03T03:37:23.907796Z","iopub.execute_input":"2021-08-03T03:37:23.908597Z","iopub.status.idle":"2021-08-03T03:38:25.244029Z","shell.execute_reply.started":"2021-08-03T03:37:23.908536Z","shell.execute_reply":"2021-08-03T03:38:25.242954Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"##### Converting Labels to Categorical Format\ny_train_ohot = tf.keras.utils.to_categorical(y_train)","metadata":{"execution":{"iopub.status.busy":"2021-08-03T03:38:25.245703Z","iopub.execute_input":"2021-08-03T03:38:25.24603Z","iopub.status.idle":"2021-08-03T03:38:25.2531Z","shell.execute_reply.started":"2021-08-03T03:38:25.245984Z","shell.execute_reply":"2021-08-03T03:38:25.252116Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"##### Plotting and Testing the Dataset\n\nfor i in range(1000,1010):\n    print(y_train[i])\n    plt.plot(np.arange(1280),X_train[i])\n    plt.show()","metadata":{"execution":{"iopub.status.busy":"2021-08-03T03:38:35.92783Z","iopub.execute_input":"2021-08-03T03:38:35.928391Z","iopub.status.idle":"2021-08-03T03:38:37.447047Z","shell.execute_reply.started":"2021-08-03T03:38:35.928358Z","shell.execute_reply":"2021-08-03T03:38:37.446083Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"### Testing Data","metadata":{}},{"cell_type":"code","source":"###### Saving Numpy Arrays\nnp.savez_compressed('./X_train_CD_EMP_test.npz',np.array(X_train))\nnp.savez_compressed('./y_train_CD_EMP_test.npz',np.array(y_train))\nnp.savez_compressed('./X_dev_CD_EMP_test.npz',np.array(X_dev))\nnp.savez_compressed('./y_dev_CD_EMP_test.npz',np.array(y_dev))","metadata":{"execution":{"iopub.status.busy":"2021-08-03T05:07:44.356797Z","iopub.execute_input":"2021-08-03T05:07:44.357285Z","iopub.status.idle":"2021-08-03T05:07:47.896121Z","shell.execute_reply.started":"2021-08-03T05:07:44.357167Z","shell.execute_reply":"2021-08-03T05:07:47.894783Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"code","source":"##### Loading Dataset - Testing Dataset\nX_train = np.array(np.load('../input/cd-emp-test/X_train_CD_EMP_test.npz',allow_pickle=True)['arr_0'],dtype=np.float16)\nX_dev = np.array(np.load('../input/cd-emp-test/X_dev_CD_EMP_test.npz',allow_pickle=True)['arr_0'],dtype=np.float16)\ny_train = np.load('../input/cd-emp-test/y_train_CD_EMP_test.npz',allow_pickle=True)['arr_0']\ny_dev = np.load('../input/cd-emp-test/y_dev_CD_EMP_test.npz',allow_pickle=True)['arr_0']","metadata":{"execution":{"iopub.status.busy":"2021-09-08T18:30:26.567747Z","iopub.execute_input":"2021-09-08T18:30:26.568113Z","iopub.status.idle":"2021-09-08T18:30:29.067881Z","shell.execute_reply.started":"2021-09-08T18:30:26.568081Z","shell.execute_reply":"2021-09-08T18:30:29.066997Z"},"trusted":true},"execution_count":4,"outputs":[]},{"cell_type":"code","source":"##### Converting Labels to Categorical Format\ny_train_ohot = tf.keras.utils.to_categorical(y_train)\ny_dev_ohot = tf.keras.utils.to_categorical(y_dev)","metadata":{"execution":{"iopub.status.busy":"2021-09-08T18:30:33.478477Z","iopub.execute_input":"2021-09-08T18:30:33.478856Z","iopub.status.idle":"2021-09-08T18:30:33.485323Z","shell.execute_reply.started":"2021-09-08T18:30:33.478823Z","shell.execute_reply":"2021-09-08T18:30:33.484097Z"},"trusted":true},"execution_count":5,"outputs":[]},{"cell_type":"markdown","source":"# Model Making","metadata":{}},{"cell_type":"markdown","source":"## Self-Calibrated Convolution","metadata":{}},{"cell_type":"code","source":"###### Model Development : Self-Calibrated \n\n##### Defining Self-Calibrated Block\n\nrate_regularizer = 1e-5\nclass self_cal_Conv1D(tf.keras.layers.Layer):\n\n    \"\"\" \n    This is inherited class from keras.layers and shall be instatition of self-calibrated convolutions\n    \"\"\"\n    \n    def __init__(self,num_filters,kernel_size,num_features):\n    \n        #### Defining Essentials\n        super().__init__()\n        self.num_filters = num_filters\n        self.kernel_size = kernel_size\n        self.num_features = num_features # Number of Channels in Input\n\n        #### Defining Layers\n        self.conv2 = tf.keras.layers.Conv1D(self.num_features/2,self.kernel_size,padding='same',kernel_regularizer=tf.keras.regularizers.l2(rate_regularizer),dtype='float32',activation='relu')\n        self.conv3 = tf.keras.layers.Conv1D(self.num_features/2,self.kernel_size,padding='same',kernel_regularizer=tf.keras.regularizers.l2(rate_regularizer),dtype='float32',activation='relu')\n        self.conv4 = tf.keras.layers.Conv1D(self.num_filters/2,self.kernel_size,padding='same',activation='relu',kernel_regularizer=tf.keras.regularizers.l2(rate_regularizer),dtype='float32')\n        self.conv1 = tf.keras.layers.Conv1D(self.num_filters/2,self.kernel_size,padding='same',activation='relu',kernel_regularizer=tf.keras.regularizers.l2(rate_regularizer),dtype='float32')\n        self.upsample = tf.keras.layers.Conv1DTranspose(filters=int(self.num_features/2),kernel_size=5,strides=5)\n        #self.attention_layer = tf.keras.layers.Attention()\n        #self.lstm = tf.keras.layers.LSTM(int(self.num_features/2),return_sequences=True)\n        #self.layernorm = tf.keras.layers.LayerNormalization()\n    \n    def get_config(self):\n\n        config = super().get_config().copy()\n        config.update({\n            'num_filters': self.num_filters,\n            'kernel_size': self.kernel_size,\n            'num_features': self.num_features\n        })\n        return config\n    \n    \n    def call(self,X):\n       \n        \"\"\"\n          INPUTS : 1) X - Input Tensor of shape (batch_size,sequence_length,num_features)\n          OUTPUTS : 1) X - Output Tensor of shape (batch_size,sequence_length,num_features)\n        \"\"\"\n        \n        #### Dimension Extraction\n        b_s = (X.shape)[0] \n        seq_len = (X.shape)[1]\n        num_features = (X.shape)[2]\n        \n        #### Channel-Wise Division\n        X_attention = X[:,:,0:int(self.num_features/2)]\n        X_global = X[:,:,int(self.num_features/2):]\n        \n        #### Self Calibration Block\n\n        ### Local Feature Detection\n\n        ## Down-Sampling\n        #x1 = X_attention[:,0:int(seq_len/5),:]\n        #x2 = X_attention[:,int(seq_len/5):int(seq_len*(2/5)),:]\n        #x3 = X_attention[:,int(seq_len*(2/5)):int(seq_len*(3/5)),:]\n        #x4 = X_attention[:,int(seq_len*(3/5)):int(seq_len*(4/5)),:]\n        #x5 = X_attention[:,int(seq_len*(4/5)):seq_len,:]\n        x_down_sampled = tf.keras.layers.AveragePooling1D(pool_size=5,strides=5)(X_attention)\n        \n        ## Convoluting Down Sampled Sequence \n        #x1 = self.conv2(x1)\n        #x2 = self.conv2(x2)\n        #x3 = self.conv2(x3)\n        #x4 = self.conv2(x4)\n        #x5 = self.conv2(x5)\n        x_down_conv = self.conv2(x_down_sampled)\n        #x_down_feature = self.attention_layer([x_down_sampled,x_down_sampled])\n        #x_down_feature = self.lstm(x_down_sampled)\n        #x_down_feature = self.layernorm(x_down_feature)\n        \n        ## Up-Sampling\n        x_down_upsampled = self.upsample(x_down_conv)   \n        #X_local_upsampled = tf.keras.layers.concatenate([x1,x2,x3,x4,x5],axis=1)\n\n        ## Local-CAM\n        X_local = X_attention + x_down_upsampled  #X_local_upsampled\n\n        ## Local Importance \n        X_2 = tf.keras.activations.sigmoid(X_local)\n\n        ### Self-Calibration\n\n        ## Global Convolution\n        X_3 = self.conv3(X_attention)\n\n        ## Attention Determination\n        X_attention = tf.math.multiply(X_2,X_3)\n\n        #### Self-Calibration Feature Extraction\n        X_4 = self.conv4(X_attention)\n\n        #### Normal Feature Extraction\n        X_1 = self.conv1(X_global)\n\n        #### Concatenating and Returning Output\n        return (tf.keras.layers.concatenate([X_1,X_4],axis=2))","metadata":{"execution":{"iopub.status.busy":"2021-09-08T18:30:47.700461Z","iopub.execute_input":"2021-09-08T18:30:47.700808Z","iopub.status.idle":"2021-09-08T18:30:47.719286Z","shell.execute_reply.started":"2021-09-08T18:30:47.700777Z","shell.execute_reply":"2021-09-08T18:30:47.718319Z"},"trusted":true},"execution_count":6,"outputs":[]},{"cell_type":"markdown","source":"## Transformer","metadata":{}},{"cell_type":"code","source":"def get_angles(pos, i, d_model):\n    angle_rates = 1 / np.power(10000, (2 * (i//2)) / np.float32(d_model))\n    return pos * angle_rates\n\ndef positional_encoding(position, d_model):\n    angle_rads = get_angles(np.arange(position)[:, np.newaxis],\n                          np.arange(d_model)[np.newaxis, :],\n                          d_model)\n  \n  # apply sin to even indices in the array; 2i\n    angle_rads[:, 0::2] = np.sin(angle_rads[:, 0::2])\n  \n  # apply cos to odd indices in the array; 2i+1\n    angle_rads[:, 1::2] = np.cos(angle_rads[:, 1::2])\n    \n    pos_encoding = angle_rads[np.newaxis, ...]\n    \n    return tf.cast(pos_encoding, dtype=tf.float32)\n\ndef create_padding_mask(seq):\n    seq = tf.cast(tf.math.equal(seq, 0), tf.float32)\n  \n    # add extra dimensions to add the padding\n    # to the attention logits. \n    return seq[:, tf.newaxis, tf.newaxis, :]  # (batch_size, 1, 1, seq_len)\n\ndef scaled_dot_product_attention(q, k, v, mask):\n    \"\"\"Calculate the attention weights.\n    q, k, v must have matching leading dimensions.\n    k, v must have matching penultimate dimension, i.e.: seq_len_k = seq_len_v.\n    The mask has different shapes depending on its type(padding or look ahead) \n    but it must be broadcastable for addition.\n\n    Args:\n    q: query shape == (..., seq_len_q, depth)\n    k: key shape == (..., seq_len_k, depth)\n    v: value shape == (..., seq_len_v, depth_v)\n    mask: Float tensor with shape broadcastable \n          to (..., seq_len_q, seq_len_k). Defaults to None.\n\n    Returns:\n    output, attention_weights\n    \"\"\"\n\n    matmul_qk = tf.matmul(q, k, transpose_b=True)  # (..., seq_len_q, seq_len_k)\n  \n    # scale matmul_qk\n    dk = tf.cast(tf.shape(k)[-1], tf.float32)\n    scaled_attention_logits = matmul_qk / tf.math.sqrt(dk)\n\n    # add the mask to the scaled tensor.\n    if mask is not None:\n        scaled_attention_logits += (mask * -1e9)  \n\n    # softmax is normalized on the last axis (seq_len_k) so that the scores\n    # add up to 1.\n    attention_weights = tf.nn.softmax(scaled_attention_logits, axis=-1)  # (..., seq_len_q, seq_len_k)\n\n    output = tf.matmul(attention_weights, v)  # (..., seq_len_q, depth_v)\n\n    return output, attention_weights\n\nclass MultiHeadAttention(tf.keras.layers.Layer):\n    \n    def __init__(self, d_model, num_heads):\n        super(MultiHeadAttention, self).__init__()\n        self.num_heads = num_heads\n        self.d_model = d_model\n\n        assert d_model % self.num_heads == 0\n\n        self.depth = d_model // self.num_heads\n\n        self.wq = tf.keras.layers.Dense(d_model)\n        self.wk = tf.keras.layers.Dense(d_model)\n        self.wv = tf.keras.layers.Dense(d_model)\n\n        self.dense = tf.keras.layers.Dense(d_model)\n\n    def get_config(self):\n        config = super(MultiHeadAttention, self).get_config().copy()\n        config.update({\n            'd_model': self.d_model,\n            'num_heads':self.num_heads\n        })\n        \n    def split_heads(self, x, batch_size):\n        \n        \"\"\"Split the last dimension into (num_heads, depth).\n        Transpose the result such that the shape is (batch_size, num_heads, seq_len, depth)\n        \"\"\"\n        x = tf.reshape(x, (batch_size, -1, self.num_heads, self.depth))\n        return tf.transpose(x, perm=[0, 2, 1, 3])\n    \n    def call(self, v, k, q, mask):\n        batch_size = tf.shape(q)[0]\n\n        q = self.wq(q)  # (batch_size, seq_len, d_model)\n        k = self.wk(k)  # (batch_size, seq_len, d_model)\n        v = self.wv(v)  # (batch_size, seq_len, d_model)\n\n        q = self.split_heads(q, batch_size)  # (batch_size, num_heads, seq_len_q, depth)\n        k = self.split_heads(k, batch_size)  # (batch_size, num_heads, seq_len_k, depth)\n        v = self.split_heads(v, batch_size)  # (batch_size, num_heads, seq_len_v, depth)\n\n        # scaled_attention.shape == (batch_size, num_heads, seq_len_q, depth)\n        # attention_weights.shape == (batch_size, num_heads, seq_len_q, seq_len_k)\n        scaled_attention, attention_weights = scaled_dot_product_attention(\n            q, k, v, mask)\n\n        scaled_attention = tf.transpose(scaled_attention, perm=[0, 2, 1, 3])  # (batch_size, seq_len_q, num_heads, depth)\n\n        concat_attention = tf.reshape(scaled_attention, \n                                      (batch_size, -1, self.d_model))  # (batch_size, seq_len_q, d_model)\n\n        output = self.dense(concat_attention)  # (batch_size, seq_len_q, d_model)\n\n        return output, attention_weights\n\ndef point_wise_feed_forward_network(d_model, dff):\n    return tf.keras.Sequential([\n      tf.keras.layers.Dense(dff, activation='relu'),  # (batch_size, seq_len, dff)\n      tf.keras.layers.Dense(d_model)  # (batch_size, seq_len, d_model)\n  ])\n\nclass Encoder(tf.keras.layers.Layer):\n    def __init__(self, num_layers, d_model, num_heads, dff,\n               maximum_position_encoding, rate=0.1):\n        super(Encoder, self).__init__()\n\n        self.d_model = d_model\n        self.num_layers = num_layers\n        self.num_heads = num_heads\n        self.dff = dff\n        self.maximum_position_encoding = maximum_position_encoding\n        self.rate = rate\n\n        #self.embedding = tf.keras.layers.Embedding(input_vocab_size, d_model)\n        self.pos_encoding = positional_encoding(maximum_position_encoding, \n                                                self.d_model)\n\n\n        self.enc_layers = [EncoderLayer(d_model, num_heads, dff, rate) \n                           for _ in range(num_layers)]\n\n        self.dropout = tf.keras.layers.Dropout(rate)\n        \n    def get_config(self):\n        config = super(Encoder, self).get_config().copy()\n        config.update({\n            'num_layers': self.num_layers,\n            'd_model': self.d_model,\n            'num_heads':self.num_heads,\n            'dff':self.dff,\n            'maximum_position_encoding':self.maximum_position_encoding,\n            'rate':self.rate  \n        })\n        \n    def call(self, x, training, mask):\n\n        seq_len = tf.shape(x)[1]\n\n        # adding embedding and position encoding.\n        #x = self.embedding(x)  # (batch_size, input_seq_len, d_model)\n        x *= tf.math.sqrt(tf.cast(self.d_model, tf.float32))\n        x += self.pos_encoding[:, :seq_len, :]\n\n        x = self.dropout(x, training=training)         \n\n        for i in range(self.num_layers):\n            x = self.enc_layers[i](x, training, mask)\n\n        return x  # (batch_size, input_seq_len, d_model)\n\nclass EncoderLayer(tf.keras.layers.Layer):\n    def __init__(self, d_model, num_heads, dff, rate=0.1):\n        super(EncoderLayer, self).__init__()\n        \n        self.d_model = d_model\n        self.num_heads = num_heads\n        self.dff = dff\n        self.rate = rate\n\n        self.mha = MultiHeadAttention(d_model, num_heads)\n        self.ffn = point_wise_feed_forward_network(d_model, dff)\n\n        self.layernorm1 = tf.keras.layers.LayerNormalization(epsilon=1e-6)\n        self.layernorm2 = tf.keras.layers.LayerNormalization(epsilon=1e-6)\n\n        self.dropout1 = tf.keras.layers.Dropout(rate)\n        self.dropout2 = tf.keras.layers.Dropout(rate)\n        \n    def get_config(self):\n        config = super(EncoderLayer, self).get_config().copy()\n        config.update({\n            'd_model': self.d_model,\n            'num_heads':self.num_heads,\n            'dff':self.dff,\n            'rate':self.rate  \n        })\n        \n    def call(self, x, training, mask):\n\n        attn_output, _ = self.mha(x, x, x, mask)  # (batch_size, input_seq_len, d_model)\n        attn_output = self.dropout1(attn_output, training=training)\n        out1 = self.layernorm1(x + attn_output)  # (batch_size, input_seq_len, d_model)\n\n        ffn_output = self.ffn(out1)  # (batch_size, input_seq_len, d_model)\n        ffn_output = self.dropout2(ffn_output, training=training)\n        out2 = self.layernorm2(out1 + ffn_output)  # (batch_size, input_seq_len, d_model)\n    \n        return out2\n    \nclass Transformer(tf.keras.Model):\n    def __init__(self, num_layers, d_model, num_heads, dff, \n                 pe_input, rate=0.1):\n        super(Transformer, self).__init__()\n        \n        self.num_layers = num_layers\n        self.d_model = d_model\n        self.num_heads = num_heads\n        self.dff = dff\n        self.pe_input = pe_input\n        self.rate = rate\n        \n        self.encoder = Encoder(num_layers, d_model, num_heads, dff, \n                                pe_input, rate)\n        \n    def get_config(self):\n        config = super(Transformer,self).get_config().copy()\n        config.update({\n            'num_layers': self.num_layers,\n            'd_model': self.d_model,\n            'num_heads':self.num_heads,\n            'dff':self.dff,\n            'pe_input':self.pe_input,\n            'rate':self.rate  \n        })\n    \n    def call(self, inp, training, enc_padding_mask):\n        return self.encoder(inp, training, enc_padding_mask)","metadata":{"execution":{"iopub.status.busy":"2021-09-08T18:30:53.889901Z","iopub.execute_input":"2021-09-08T18:30:53.890270Z","iopub.status.idle":"2021-09-08T18:30:53.934455Z","shell.execute_reply.started":"2021-09-08T18:30:53.890231Z","shell.execute_reply":"2021-09-08T18:30:53.933663Z"},"trusted":true},"execution_count":7,"outputs":[]},{"cell_type":"markdown","source":"## ArcFace Loss","metadata":{}},{"cell_type":"code","source":"class ArcFace(tf.keras.layers.Layer):\n    \n    def __init__(self, n_classes, s, m,regularizer):\n        super().__init__()\n        self.n_classes = n_classes\n        self.s = s\n        self.m = m\n        self.regularizer = tf.keras.regularizers.get(regularizer)\n\n    def get_config(self):\n\n        config = super().get_config().copy()\n        config.update({\n            'n_classes': self.n_classes,\n            's': self.s,\n            'm': self.m,\n            'regularizer': self.regularizer\n        })\n        return config\n\n    def build(self, input_shape):\n        super(ArcFace, self).build(input_shape[0])\n        self.W = self.add_weight(name='W',\n                                shape=(input_shape[0][-1], self.n_classes),\n                                initializer='glorot_uniform',\n                                trainable=True\n                                )\n\n    def call(self, inputs):\n        x, y = inputs\n        c = tf.keras.backend.shape(x)[-1]\n        # normalize feature\n        x = tf.nn.l2_normalize(x, axis=1)\n        # normalize weights\n        W = tf.nn.l2_normalize(self.W, axis=0)\n        # dot product\n        logits = x @ W\n        # add margin\n        # clip logits to prevent zero division when backward\n        theta = tf.acos(tf.keras.backend.clip(logits, -1.0 + tf.keras.backend.epsilon(), 1.0 - tf.keras.backend.epsilon()))\n        target_logits = tf.cos(theta + self.m)\n        # sin = tf.sqrt(1 - logits**2)\n        # cos_m = tf.cos(logits)\n        # sin_m = tf.sin(logits)\n        # target_logits = logits * cos_m - sin * sin_m\n        #\n        logits = logits * (1 - y) + target_logits * y\n        # feature re-scale\n        logits *= self.s\n        out = tf.nn.softmax(logits)    \n        return out\n\n    def compute_output_shape(self, input_shape):\n        return (None, self.n_classes)","metadata":{"execution":{"iopub.status.busy":"2021-09-08T18:31:03.137519Z","iopub.execute_input":"2021-09-08T18:31:03.138029Z","iopub.status.idle":"2021-09-08T18:31:03.151213Z","shell.execute_reply.started":"2021-09-08T18:31:03.137994Z","shell.execute_reply":"2021-09-08T18:31:03.150378Z"},"trusted":true},"execution_count":8,"outputs":[]},{"cell_type":"markdown","source":"# Model Training","metadata":{}},{"cell_type":"code","source":"## Phase-1 Models\n###### Defining Architecture\n\nwith tpu_strategy.scope():\n\n    ##### SC_Module \n\n    #### Defining Hyperparameters\n    num_layers = 2\n    d_model = 512\n    num_heads = 8\n    dff = 1024\n    max_seq_len = 1280 #X_train.shape[1]\n    pe_input = 320\n    rate = 0.5\n    num_features = 1\n    num_classes = 20\n\n    #### Defining Layers\n    Input_layer = tf.keras.layers.Input(shape=(max_seq_len,num_features))\n    self_conv1 = self_cal_Conv1D(128,15,128)\n    self_conv2 = self_cal_Conv1D(128,20,128) # Newly Added\n    self_conv3 = self_cal_Conv1D(256,15,128)\n    self_conv4 = self_cal_Conv1D(256,20,256) # Newly Added\n    self_conv5 = self_cal_Conv1D(512,15,256)\n    self_conv6 = self_cal_Conv1D(512,20,512) # Newly Added\n    self_conv7 = self_cal_Conv1D(1024,15,512)\n    self_conv8 = self_cal_Conv1D(1024,20,1024) # Newly Added\n    conv_initial = tf.keras.layers.Conv1D(32,15,padding='same',activation='relu')\n    conv_second = tf.keras.layers.Conv1D(64,15,padding='same',activation='relu')\n    conv_third = tf.keras.layers.Conv1D(128,15,padding='same',activation='relu')\n    #lstm1 = tf.keras.layers.Bidirectional(tf.keras.layers.LSTM(128,activation='tanh',return_sequences=True),merge_mode='ave')\n    transform_1 = tf.keras.layers.Conv1D(128,3,padding='same',kernel_initializer='lecun_normal', activation='selu')\n    transform_2 = tf.keras.layers.Conv1D(256,3,padding='same',kernel_initializer='lecun_normal', activation='selu')\n    transform_3 = tf.keras.layers.Conv1D(512,3,padding='same',kernel_initializer='lecun_normal', activation='selu')\n    transform_4 = tf.keras.layers.Conv1D(1024,3,padding='same',kernel_initializer='lecun_normal', activation='selu')\n    transformer = Transformer(num_layers,d_model,num_heads,dff,pe_input,rate)\n    gap_layer = tf.keras.layers.GlobalAveragePooling1D()\n    arc_logit_layer = ArcFace(20,30.0,0.3,tf.keras.regularizers.l2(1e-4))\n\n    #### Defining Architecture\n    ### Input Layer\n    Inputs = Input_layer\n    Input_Labels = tf.keras.layers.Input(shape=(num_classes,))\n\n    ### Initial Convolutional Layers\n    conv_initial = conv_initial(Inputs)\n    #conv_initial = tf.keras.layers.LayerNormalization()(conv_initial)\n    #conv_initial = tf.keras.layers.MaxPool1D(pool_size=2,strides=2)(conv_initial)     \n    #conv_initial = tf.keras.layers.Add()([conv_initial,Inputs])\n    \n    conv_second = conv_second(conv_initial)\n    #conv_second = tf.keras.layers.LayerNormalization()(conv_second)\n    #conv_second = tf.keras.layers.MaxPool1D(pool_size=2,strides=2)(conv_second)\n    #conv_second = tf.keras.layers.Add()([conv_second,conv_initial])\n    #conv_second = tf.keras.layers.concatenate(axis=2)([conv_initial,conv_second])\n    \n    conv_third = conv_third(conv_second)\n    #conv_third = tf.keras.layers.LayerNormalization()(conv_third)\n    #conv_third = tf.keras.layers.MaxPool1D(pool_size=2,strides=2)(conv_third)\n    #mask = tf.keras.layers.MaxPool1D(pool_size=2,strides=2)(Inputs)\n    #conv_third = tf.keras.layers.Add()([conv_third,conv_second])\n    #conv_third = tf.keras.layers.concatenate(axis=2)([conv_initial,conv_second,conv_third])\n    #conv_third = lstm1(conv_second)\n    #conv_third = tf.keras.layers.Attention()([conv_third,conv_third])\n    \n    ### 1st Residual Block\n    transform_1 = transform_1(conv_third)\n    conv1 = self_conv1(conv_third)\n    #conv1 = tf.keras.layers.AlphaDropout(rate=0.2)(conv1)\n    conv2 = self_conv2(conv1)\n    #conv2 = tf.keras.layers.AlphaDropout(rate=0.2)(conv2)\n    conv2 = tf.keras.layers.Add()([conv2,transform_1])\n    #conv2 = tf.keras.layers.LayerNormalization()(conv2)\n    conv2 = tf.keras.layers.MaxPool1D(pool_size=2,strides=2)(conv2)\n    #mask = tf.keras.layers.MaxPool1D(pool_size=2,strides=2)(mask)    \n\n    ### 2nd Residual Block\n    #conv_third = tf.keras.layers.Attention()([conv_third,conv_third])\n    transform_2 = transform_2(conv2)\n    conv3 = self_conv3(conv2)\n    #conv3 = tf.keras.layers.AlphaDropout(rate=0.2)(conv3)\n    conv4 = self_conv4(conv3)\n    #conv4 = tf.keras.layers.AlphaDropout(rate=0.2)(conv4)\n    conv4 = tf.keras.layers.Add()([conv4,transform_2])\n    #conv4 = tf.keras.layers.LayerNormalization()(conv4)\n    conv4 = tf.keras.layers.MaxPool1D(pool_size=2,strides=2)(conv4)\n    #mask = tf.keras.layers.MaxPool1D(pool_size=2,strides=2)(mask)\n\n    ### 3rd Residual Block\n    transform_3 = transform_3(conv4)\n    conv5 = self_conv5(conv4)\n    #conv5 = tf.keras.layers.AlphaDropout(rate=0.2)(conv5)\n    conv6 = self_conv6(conv5)\n    #conv6 = tf.keras.layers.AlphaDropout(rate=0.2)(conv6)\n    conv6 = tf.keras.layers.Add()([conv6,transform_3])\n    #conv6 = tf.keras.layers.LayerNormalization()(conv6)\n    #conv6 = tf.keras.layers.MaxPool1D(pool_size=2,strides=2)(conv6)\n\n    ### 4th Residual Block\n    #transform_4 = transform_4(conv6)\n    #conv7 = self_conv7(conv6)\n    #conv8 = self_conv8(conv7)\n    #conv8 = tf.keras.layers.Add()([conv8,transform_4])\n\n    ### Transformer\n    ## Wide-Head Attention Model\n    #tx_embedding = tf.keras.layers.Lambda(PE_Layer)(Inputs)\n    #tx_embedding = tf.keras.layers.Dropout(rate)(tx_embedding,training=True)\n    #mask_reshaped = tf.keras.layers.Reshape((max_seq_len,))(Inputs)\n    #encoder_op1 = encoder_block1(tx_embedding,mask_reshaped)\n    #encoder_op2 = encoder_block2(encoder_op1,mask_reshaped)\n\n    ## Narrow-Head Attention Model\n    #mask_reshaped = tf.keras.layers.Reshape((160,))(mask)\n    embeddings =  transformer(inp=conv6,enc_padding_mask=None)\n    #embeddings = transformer(inp=conv6,enc_padding_mask=create_padding_mask(mask))\n    #residual_embeddings = tf.keras.layers.Add()([conv6,embeddings])\n\n    ### Output Layers\n    ## Initial Layers\n    gap_op = gap_layer(embeddings)\n    dense1 = tf.keras.layers.Dense(256,activation='relu')(gap_op)\n    dropout1 = tf.keras.layers.Dropout(rate)(dense1)\n    \n    ## ArcFace Output Network\n    dense2 = tf.keras.layers.Dense(256,kernel_initializer='he_normal',\n                kernel_regularizer=tf.keras.regularizers.l2(1e-4))(dropout1)\n    ##dense2 = tf.keras.layers.BatchNormalization()(dense2)\n    dense3 = arc_logit_layer(([dense2,Input_Labels]))\n    \n    ## Softmax Output Network\n    #dense2 = tf.keras.layers.Dense(256,activation='relu')(dropout1)\n    ###dropout2 = tf.keras.layers.Dropout(rate)(dense2) # Not to be included\n    #dense3 = tf.keras.layers.Dense(35,activation='softmax')(dense2)\n\n    #### Compiling Architecture            \n    ### ArcFace Model Compilation\n    model = tf.keras.models.Model(inputs=[Inputs,Input_Labels],outputs=dense3)\n    model.load_weights('../input/cd-emp-test/CD_EMP.h5')\n    model.compile(tf.keras.optimizers.Adam(lr=1e-4,clipnorm=1.0),loss='categorical_crossentropy',metrics=['accuracy'])\n    ### Softmax Model Compilation\n    #model = tf.keras.models.Model(inputs=Inputs,outputs=dense3)\n\nmodel.summary()      \ntf.keras.utils.plot_model(model)\n##### Model Training \n\n#### Model Checkpointing\n#! mkdir './Models'\n#filepath= \"/content/Models/saved-model-{epoch:02d}-{val_accuracy:.2f}.h5\"\n#checkpoint = tf.keras.callbacks.ModelCheckpoint(filepath,monitor='val_accuracy',save_best_only=False,mode='max')\nfilepath = './CD_EMP.h5'\ncheckpoint = tf.keras.callbacks.ModelCheckpoint(filepath,monitor='val_accuracy',save_best_only=True,mode='max',save_weights_only=True)\n\n#### Custom Learning Rate Schedule\n#def build_lrfn(lr_start=1e-4, lr_max=1e-3, \n#               lr_min=1e-6, lr_rampup_epochs=5, \n#               lr_sustain_epochs=0, lr_exp_decay=.87):\n#    lr_max = lr_max * tpu_strategy.num_replicas_in_sync\n\n#    def lrfn(epoch):\n#        if epoch < lr_rampup_epochs:\n#            lr = (lr_max - lr_start) / lr_rampup_epochs * epoch + lr_start\n#        elif epoch < lr_rampup_epochs + lr_sustain_epochs:\n#            lr = lr_max\n#        else:\n#            lr = (lr_max - lr_min) * lr_exp_decay**(epoch - lr_rampup_epochs - lr_sustain_epochs) + lr_min#\n#        return lr\n#    \n#    return lrfn\n\n#lrfn = build_lrfn()\n#lr_callback = tf.keras.callbacks.LearningRateScheduler(lrfn, verbose=1)\n#callback_list = [checkpoint,  lr_callback]\n\n#### Model Training\n#### Model Training\n### ArcFace Training\n#history = model.fit((X_train,y_train_ohot),y_train_ohot,epochs=500,batch_size=128,\n#                validation_split=0.1,validation_batch_size=128,\n#               callbacks=checkpoint)\n\n### Softmax Training \n#history = model.fit(X_train,y_train_ohot,epochs=250,batch_size=128,\n#                validation_data=(X_dev,y_dev_ohot),validation_batch_size=128,\n#                callbacks=checkpoint)\n\n\n##### Plotting Metrics  \n#### Accuracy and Loss Plots \n\n### Accuracy\n#plt.plot(history.history['accuracy'])\n#plt.plot(history.history['val_accuracy'])\n#plt.title('Model Accuracy')\n#plt.ylabel('Accuracy')\n#plt.xlabel('Epoch')  \n#plt.legend(['Train', 'Validation'], loc='best')\n#plt.show()\n\n### Loss     \n#plt.plot(history.history['loss'])  \n#plt.plot(history.history['val_loss'])\n#plt.title('Model Loss')  \n#plt.ylabel('Loss')         \n#plt.xlabel('epoch')\n#plt.legend(['Train', 'Validation'], loc='best')   \n#plt.show()      \n\n##### Saving Model            \n#model.save_weights('ECG_SCNRNet.h5' )","metadata":{"execution":{"iopub.status.busy":"2021-09-08T18:55:31.200675Z","iopub.execute_input":"2021-09-08T18:55:31.201069Z","iopub.status.idle":"2021-09-08T18:55:37.430235Z","shell.execute_reply.started":"2021-09-08T18:55:31.201028Z","shell.execute_reply":"2021-09-08T18:55:37.429037Z"},"trusted":true},"execution_count":51,"outputs":[{"name":"stdout","text":"Model: \"model_12\"\n__________________________________________________________________________________________________\nLayer (type)                    Output Shape         Param #     Connected to                     \n==================================================================================================\ninput_15 (InputLayer)           [(None, 1280, 1)]    0                                            \n__________________________________________________________________________________________________\nconv1d_110 (Conv1D)             (None, 1280, 32)     512         input_15[0][0]                   \n__________________________________________________________________________________________________\nconv1d_111 (Conv1D)             (None, 1280, 64)     30784       conv1d_110[0][0]                 \n__________________________________________________________________________________________________\nconv1d_112 (Conv1D)             (None, 1280, 128)    123008      conv1d_111[0][0]                 \n__________________________________________________________________________________________________\nself_cal__conv1d_16 (self_cal_C (None, 1280, 128)    266560      conv1d_112[0][0]                 \n__________________________________________________________________________________________________\nself_cal__conv1d_17 (self_cal_C (None, 1280, 128)    348480      self_cal__conv1d_16[0][0]        \n__________________________________________________________________________________________________\nconv1d_113 (Conv1D)             (None, 1280, 128)    49280       conv1d_112[0][0]                 \n__________________________________________________________________________________________________\nadd_6 (Add)                     (None, 1280, 128)    0           self_cal__conv1d_17[0][0]        \n                                                                 conv1d_113[0][0]                 \n__________________________________________________________________________________________________\nmax_pooling1d_4 (MaxPooling1D)  (None, 640, 128)     0           add_6[0][0]                      \n__________________________________________________________________________________________________\nself_cal__conv1d_18 (self_cal_C (None, 640, 256)     389568      max_pooling1d_4[0][0]            \n__________________________________________________________________________________________________\nself_cal__conv1d_19 (self_cal_C (None, 640, 256)     1393280     self_cal__conv1d_18[0][0]        \n__________________________________________________________________________________________________\nconv1d_114 (Conv1D)             (None, 640, 256)     98560       max_pooling1d_4[0][0]            \n__________________________________________________________________________________________________\nadd_7 (Add)                     (None, 640, 256)     0           self_cal__conv1d_19[0][0]        \n                                                                 conv1d_114[0][0]                 \n__________________________________________________________________________________________________\nmax_pooling1d_5 (MaxPooling1D)  (None, 320, 256)     0           add_7[0][0]                      \n__________________________________________________________________________________________________\nself_cal__conv1d_20 (self_cal_C (None, 320, 512)     1557376     max_pooling1d_5[0][0]            \n__________________________________________________________________________________________________\nself_cal__conv1d_21 (self_cal_C (None, 320, 512)     5571840     self_cal__conv1d_20[0][0]        \n__________________________________________________________________________________________________\nconv1d_115 (Conv1D)             (None, 320, 512)     393728      max_pooling1d_5[0][0]            \n__________________________________________________________________________________________________\nadd_8 (Add)                     (None, 320, 512)     0           self_cal__conv1d_21[0][0]        \n                                                                 conv1d_115[0][0]                 \n__________________________________________________________________________________________________\ntransformer_2 (Transformer)     (None, 320, 512)     4205568     add_8[0][0]                      \n__________________________________________________________________________________________________\nglobal_average_pooling1d_2 (Glo (None, 512)          0           transformer_2[0][0]              \n__________________________________________________________________________________________________\ndense_40 (Dense)                (None, 256)          131328      global_average_pooling1d_2[0][0] \n__________________________________________________________________________________________________\ndropout_17 (Dropout)            (None, 256)          0           dense_40[0][0]                   \n__________________________________________________________________________________________________\ndense_41 (Dense)                (None, 256)          65792       dropout_17[0][0]                 \n__________________________________________________________________________________________________\ninput_16 (InputLayer)           [(None, 20)]         0                                            \n__________________________________________________________________________________________________\narc_face_2 (ArcFace)            (None, 20)           5120        dense_41[0][0]                   \n                                                                 input_16[0][0]                   \n==================================================================================================\nTotal params: 14,630,784\nTrainable params: 14,630,784\nNon-trainable params: 0\n__________________________________________________________________________________________________\n","output_type":"stream"}]},{"cell_type":"markdown","source":"# Model Testing","metadata":{}},{"cell_type":"markdown","source":"## KNN based ArcFace Loss Testing","metadata":{}},{"cell_type":"code","source":"###### Testing Model - ArcFace Style                \nwith tpu_strategy.scope():     \n\n    def normalisation_layer(x):   \n        return(tf.math.l2_normalize(x, axis=1, epsilon=1e-12))\n\n    #X_dev_flipped = tf.image.flip_up_down(X_dev)  \n    #x_train_flipped = tf.image.flip_up_down(X_train_final)\n\n    predictive_model = tf.keras.models.Model(inputs=model.input,outputs=model.layers[-3].output)\n    predictive_model.compile(tf.keras.optimizers.Adam(lr=1e-4),loss='categorical_crossentropy',metrics=['accuracy'])\n\nwith tpu_strategy.scope():\n    y_in = tf.keras.layers.Input((113,))   \n\n    Input_Layer = tf.keras.layers.Input((1280,1))\n    op_1 = predictive_model([Input_Layer,y_in])\n\n    ##Input_Layer_Flipped = tf.keras.layers.Input((224,224,3))\n    ##op_2 = predictive_model([Input_Layer_Flipped,y_in]) \n    ##final_op = tf.keras.layers.Concatenate(axis=1)(op_1)\n\n    final_norm_op = tf.keras.layers.Lambda(normalisation_layer)(op_1)\n\n    testing_model = tf.keras.models.Model(inputs=[Input_Layer,y_in],outputs=final_norm_op)\n    testing_model.compile(tf.keras.optimizers.Adam(lr=1e-4),loss='categorical_crossentropy',metrics=['accuracy'])\n\n##### Nearest Neighbor Classification\nfrom sklearn.neighbors import KNeighborsClassifier\nTest_Embeddings = testing_model.predict((X_dev,y_dev_ohot))\nTrain_Embeddings = testing_model.predict((X_train,y_train_ohot))\n\ncol_mean = np.nanmean(Test_Embeddings, axis=0)\ninds = np.where(np.isnan(Test_Embeddings))\n#print(inds)\nTest_Embeddings[inds] = np.take(col_mean, inds[1])\n\ncol_mean = np.nanmean(Train_Embeddings, axis=0)                                                                                                                                \ninds = np.where(np.isnan(Train_Embeddings))\n#print(inds)\nTrain_Embeddings[inds] = np.take(col_mean, inds[1])\n\n#Test_Embeddings = np.nan_to_num(Test_Embeddings)\n\n##### Refining Test Embeddings\n#for i in range(Train_Embeddings.shape[0]):\n#    for j in range(Train_Embeddings.shape[1]):\n#        if(math.isnan(Train_Embeddings[i,j])):\n#            Train_Embeddings[i,j] == 0\n#        if(Train_Embeddings[i,j]>1e4):\n#            Train_Embeddings[i,j] == 1e4\n\n##### Refining Train Embeddings    \n#for i in range(Test_Embeddings.shape[0]):\n#    for j in range(Test_Embeddings.shape[1]):\n#        if(math.isnan(Test_Embeddings[i,j])):\n#            Test_Embeddings[i,j] == 0\n#        if(Test_Embeddings[i,j]>1e4 or math.isinf(Test_Embeddings[i,j])):\n#            Test_Embeddings[i,j] == 1e4\n\n#del(X_train_final,X_dev,X_dev_flipped,x_train_flipped)\n#gc.collect()\n\nTest_Accuracy_With_Train = []\nTest_Accuracy_With_Test = []\n                                                                     \nfor k in range(1,31):\n    knn = KNeighborsClassifier(n_neighbors=k,metric='euclidean')\n    knn.fit(Train_Embeddings,y_train)\n    Test_Accuracy_With_Train.append(knn.score(Test_Embeddings,y_dev))\n    knn.fit(Test_Embeddings,y_dev)\n    Test_Accuracy_With_Test.append(knn.score(Test_Embeddings,y_dev))\n\nprint('--------------------------------')\nprint(np.max(Test_Accuracy_With_Train))\nprint(np.max(Test_Accuracy_With_Test))\nprint('--------------------------------')\nprint(np.mean(Test_Accuracy_With_Train))\nprint(np.mean(Test_Accuracy_With_Test))\nprint('--------------------------------')\nprint((Test_Accuracy_With_Train)[0])\nprint((Test_Accuracy_With_Test)[0])\nprint('--------------------------------')\n\nplt.plot(np.arange(1,31),np.array(Test_Accuracy_With_Train),label='Test_Accuracy_With_Train')\nplt.plot(np.arange(1,31),np.array(Test_Accuracy_With_Test),label='Test_Accuracy_With_Test')\nplt.title('Testing Accuracy vs Number of Neighbors')\nplt.xlabel('Number of Neighbors')\nplt.ylabel('Test Accuracy')\nplt.legend()       \nplt.show()                 \n\nnp.savez_compressed('Test_Embeddings_Baseline.npz',Test_Embeddings)\nnp.savez_compressed('Train_Embeddings_Baseline.npz',Train_Embeddings)","metadata":{"execution":{"iopub.status.busy":"2021-09-08T18:36:23.175161Z","iopub.execute_input":"2021-09-08T18:36:23.175571Z","iopub.status.idle":"2021-09-08T18:36:25.482505Z","shell.execute_reply.started":"2021-09-08T18:36:23.175529Z","shell.execute_reply":"2021-09-08T18:36:25.480232Z"}},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## t-SNE","metadata":{}},{"cell_type":"code","source":"####### t-SNE Plot Generation\n###### Model Creation\n#with tpu_strategy.scope():          \n#    tsne_model = tf.keras.models.Model(inputs=model.input,outputs=model.layers[-4].output)\n#    tsne_model.compile(tf.keras.optimizers.Adam(lr=1e-4),loss='categorical_crossentropy',metrics=['accuracy'])\n#tsne_model.summary()\n\n###### Model Predicted\n#embeddings_final = tsne_model.predict((X_dev,y_exp))\n\n###### t-SNE plot plotting\n##### Reduction to Lower Dimensions\ntsne_X_dev = TSNE(n_components=2,perplexity=30,learning_rate=10,n_iter=2000,n_iter_without_progress=50).fit_transform(Test_Embeddings)\n\n##### Plotting\nj = 0 # Index for rotating legend\nplt.rcParams[\"figure.figsize\"] = [24,16]\nmStyles = [\".\",\",\",\"o\",\"v\",\"^\",\"<\",\">\",\"1\",\"2\",\"3\",\"4\",\"8\",\"s\",\"p\",\"P\",\"*\",\"h\",\"H\",\"+\",\"x\",\"X\",\"D\",\"d\",\"|\",\"_\",\n           0,1,2,3,4,5,6,7,8,9,10,11,0,1,2,3,4,5,6,7,8,9,10]\nfor idx,color_index,marker_type in zip(list(np.arange(100)),sns.color_palette('muted',100),mStyles):\n    plt.scatter(tsne_X_dev[y_dev == idx, 0], tsne_X_dev[y_dev == idx, 1],marker=marker_type)\nplt.legend([str(j) for j in range(100)])\nplt.savefig('tsne_plot_5000_iters.png')\nplt.savefig('tsne_plot_5000_iters.pdf')\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2021-08-03T05:20:50.546255Z","iopub.execute_input":"2021-08-03T05:20:50.546572Z","iopub.status.idle":"2021-08-03T05:21:26.686492Z","shell.execute_reply.started":"2021-08-03T05:20:50.546541Z","shell.execute_reply":"2021-08-03T05:21:26.684976Z"},"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"## Data Variability Analysis using t-SNE plots","metadata":{}},{"cell_type":"code","source":"####### Sampling Examples from t-SNE plots\n\n###### Defining Essentials \nX_train_va = [] # va for variabiltiy analysis\nX_dev_va = []\ny_va = [] # Training and Testing Dataset Share the same labels\n\n##### Training Dataset\nfor class_idx in list(np.arange(60,80)): # Selection of Class\n    \n    total_items = 0 # Variable to monitor the Number of Samples in the va set\n    \n    for i in range(X_train.shape[0]): # Looping over the Training Dataset    \n        \n        if(total_items < 5):\n            \n            if(y_train[i] == class_idx):\n                X_train_va.append(X_train[i])\n                y_va.append(class_idx-60)\n                \n                total_items = total_items+1\n    \n##### Testing Dataset\nfor class_idx in list(np.arange(60,80)): # Selection of Class\n    \n    total_items = 0 # Variable to monitor the Number of Samples in the va set\n    \n    for i in range(X_dev.shape[0]): # Looping over the Training Dataset    \n        \n        if(total_items < 5):\n            \n            if(y_dev[i] == class_idx):\n                X_dev_va.append(X_dev[i])\n                #y_va.appenf(class_idx)\n                \n                total_items = total_items+1","metadata":{"execution":{"iopub.status.busy":"2021-09-08T19:10:52.241254Z","iopub.execute_input":"2021-09-08T19:10:52.241614Z","iopub.status.idle":"2021-09-08T19:10:52.270799Z","shell.execute_reply.started":"2021-09-08T19:10:52.241584Z","shell.execute_reply":"2021-09-08T19:10:52.269995Z"},"trusted":true},"execution_count":80,"outputs":[]},{"cell_type":"code","source":"###### Inferring Data Shape\nprint(np.array(X_train_va).shape)\nprint(np.array(X_dev_va).shape)\nprint(np.array(y_va).shape)","metadata":{"execution":{"iopub.status.busy":"2021-09-08T19:10:54.280418Z","iopub.execute_input":"2021-09-08T19:10:54.280758Z","iopub.status.idle":"2021-09-08T19:10:54.287964Z","shell.execute_reply.started":"2021-09-08T19:10:54.280726Z","shell.execute_reply":"2021-09-08T19:10:54.286931Z"},"trusted":true},"execution_count":81,"outputs":[{"name":"stdout","text":"(100, 1280, 1)\n(100, 1280, 1)\n(100,)\n","output_type":"stream"}]},{"cell_type":"code","source":"###### Plotting Data and Computing Correlation\nimport scipy.stats\n\nfor i in range(0,25,5):\n    plt.plot(np.arange(1280),X_train_va[i])\n    plt.plot(np.arange(1280),X_dev_va[i])\n    \n    X_sess1 = X_train_va[i]\n    X_sess2 = X_dev_va[i]\n    \n    r,p = scipy.stats.pearsonr(X_sess1[:,0], X_sess2[:,0])\n    \n    print('Correlation Coefficient = '+str(r))\n\n    plt.show()","metadata":{"execution":{"iopub.status.busy":"2021-09-08T19:11:00.550937Z","iopub.execute_input":"2021-09-08T19:11:00.551321Z","iopub.status.idle":"2021-09-08T19:11:01.755636Z","shell.execute_reply.started":"2021-09-08T19:11:00.551291Z","shell.execute_reply":"2021-09-08T19:11:01.754889Z"},"trusted":true},"execution_count":82,"outputs":[{"name":"stdout","text":"Correlation Coefficient = 0.08984372501779114\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"<Figure size 1728x1296 with 1 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Coefficient = 0.13065031577071723\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"<Figure size 1728x1296 with 1 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\n"},"metadata":{"needs_background":"light"}},{"name":"stdout","text":"Correlation Coefficient = 0.10954206878686487\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"<Figure size 1728x1296 with 1 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\n"},"metadata":{"needs_background":"light"}},{"name":"stdout","text":"Correlation Coefficient = 0.16178908952485616\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"<Figure size 1728x1296 with 1 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Coefficient = 0.23722810545736345\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"<Figure size 1728x1296 with 1 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x2F7M1+tc2lwv48d4DSBITaKMy0lOl8bJtv5Suf7HGyUxA5sU3xF7USZ9S3Fu1t4uQpsrp4ZKb4GPNsD86L4isr4E/H23lOSpNAZSdx0Abl87EBLO1995isDt5DL9sl8bag08zUYdMY5u84j2jDpwK1dYgdQO4PM18E1nus7sLl87MCWjx0IiB0A5kXxFZXxWwnD/cuSpCCZUG15qALGtT12INMVI/EWHSOyA7fofG0UY52CIN66mGa+0vs6vXTg1o5keus+GmBIdqCetKYuuYtPSB/80dX+nkBDHUbDma9x7ADXbGAe3XUfAJrDJjdcQRI3QOwAUKLX8tiB0c7XdR4Q6seauLPP/xiNYawb6oqTyISciUsyXzs7dL6idtLO146PFlpDPuRP/mnpxcek13y1dPy2Ff/mQLP4zNedNHYgSJ/5AcyGzldUJn7b7dKO17TzlfMzMM7HDvTa2fnaofMVZWwkdbbi7dXEDjQK639B1gw6X8l8Rc1EI7EDQbCGzvato/HXJ39ztb8v0ECjA7c6YSDDNRuYC8VXVMY4pzBzgxWIzFeg0GF7YwesUyZ2gMxX5DD9pLtvi9iBhokymc+s/zn4ztfuLsVX1M5goN6gS27l6/vWR+KvFF+BhY1mvobBGrrZgYag+IrKWOvU1WB7aEjnK5DP9CWTPDS3MHYgHrgV/zj5wksaDLNGCrfi/5lo3UeDCg11viafsf5nYKNk4NZOXIhlfaBGIjPe+bryLco+quapd6729wUaaLTzNVzHmgYaguIrKmOsUydTfA2SbiW2EwIjfOTAzikp2m/dVDrrXJr1SOYrctko3lodduh8bRhjnbqZDhqJ9T8TP3ArTMY2sD5QI/6ev5PJdV75+vYvt29cXPXvDDROz1gFweCFCrEDwPwovqIy1jl1NSgiBc6knwPI8MO2jt8af43a1f1qrcvEDiSfcZ5Als3EDpD52iiRHbx8Yf3PwRkpCOMCrCS5dr28Q73lZb6ufH37OA5LVziwqF5ktd0J05ggHyXCjhVgdhRfUZlorPM1vunh3AyM8EO2jp6Lv7YsesC4QeZj8nzGeQLD/MCtkMzXprHWpYUZ1v8c/MCtILmFp/iKGjF2uPM10BrWt+nFX50p//cATNQzcfHV82ub5AFgdhRfUZk4diDT+ZpmvnJ2Bob4bozdk/FXH0PQEsYOBm751EfOExhik6FCnS6Zlg0TDWW+sv5n5kyc+UrxFTU0yHxNokXCYPUdcnS+ApXpRTbNe5UGL00N1VdgZhRfURlbWHxd1xEBNeW7MbaPx19b1vlqnZN/iU7nG3KZfpJrucUDdMMYawfFV9b/7GwUv5jwxVdLdx/qI+187Qy2KK/8OcB3vrI2gIWNFV9DXpoC86L4isoY59TNxg44Ol+BXP6BYMcXX2+u71jWwNhB7IDPkOI0gSE2iguvHWIHmibKxA6w/ufgB24FPvOVPzzUx1jmq9aY+SrXuoGmQNV6Zrj46u/feb4HZkfxFZWx1qkT5GW+cnIGhrS98zUzcCvtfGXeObJ8d19I7EDTxJ3vrP+5pbED/g+P4hLqwyTFzk7mBcvKV7c5HPyYnRPAQvrGaquTjR2I1zaxA8DsKL6iMpF12gkGJ2JffDU8FwDDfCdGZyv+2rKH5+zArcG08zUeEOrFGkluUHyl87VRIuPGYgdY/zOwRgpDMl9RS77zNTtUc/WZr73Bjxm6BSykFw0P3Erf+63peIBNRvEVlTHOaStMHgKCTvq2mY4WYIR/WA67yc/b9XBgsgN30m3HnCeQ8J1KYSd+QWEovjZJdv2HrP/ZjQ3catf1A/VmrFMYDHIhg2ANO//pfAUqczg2cCu5bvPeD5gZxVdUxlqn7SA5E3d3FSTdSjxTASP8w3JnO/l5u+5gnBsUXZMX6HS+YcA/LHe2GLjVQMYNMl891v8MrEm6wn3ma7uuH6i3ONN5uFCz8iaMbOcrQ7eAhYwO3BrsWOHCDcyK4isqY6y07Ttft3bTGx46WoAR/mEg7Xxt18OzcU5+B5MvwrKBCam087Urdbp0vjZMXucr638G1iQDt4gdQP1k17cUr/GVv1wZ6nyl+Aosom+GYwfSztd1HRCwwSi+ojLWOW3ldb6u8ZiAWko7X33ma7tWibFuKA9Oat0fAcqYTPGVztfGIfN1QWOxAxRfUR+RyetsX0Pna7qziOIrsIieGY0diL/S+QrMjuIrKhNZO+h87e6mNzyWpypgWJr5mhRfW9SZ4c8HaR5cEjzAaQKpoc7XLQZuNUx+5us6j2jDjA7catH1A/VnrFWnk+l8DbX6LgxzKG0djX/MyztgIaMDt/xbU4qvwOwovqIyxkrdIDkRd3cVGDpfgVx++kTa+dqeziXjxichS8STICNbfA27g05YNEKc+Rrffg4yn1n/UxvrfOXPDvURZ76Oxg6s8HvUOcn0KL4CFekbl9v5ygM+MDuKr6hMPHAr6cDY2k1veOhoA0a49ma+mpHOV7HtGKN8p6svvtL52iiRzcYO0Pk6MzJfUWOjma+BVnx99xnh2774Smc4sIheZLWV6XxlxxowP4qvqIwZyXz1xVc62oAR/mGghZlkvgNmbNsxr9Dh2UwmcmeLgVsNY6zNyXxl/U/Fufh6EXYpvqKW4s7X4eE8K13dftjW1pH4K8VXYCGHUX7mK/ftwOwovqIy1uYN3HJ0tACjXItjB+xw7EC6e4nzBLw0dqDDwK0GMnb85Qum5K8VDNxCTY11vgYrfrkS9eKvW8firy16uQ0sQy8y2ukOv1CR6HwF5kHxFZWJssXX5I1zKMebMWBUGjvQSX7enodnH3frYwf8V4qvSJlM7ECnS+drwxhr00xIMl9n5Lv4sgO3KC6hRkYzX4MgWO0OON/5uk3mK1CFvnHaygzRS+PCqL4CM6P4isoMxw7sSJK2FPFmDBg1GjtgW1R8TR7CRiJfKb5gYGjg1haZrw0TWZd5+RJ/xvKfki+0Bp1WvrxD/WVjRaT4Wr/SW5zIxw6Q+QpUoWdGYwfYsQLMi+IrKjMaOyBJHVkeqoBR/mE5bGHswEjmazpwZ21HhNpJu/uSzFc6lxrFZjrjBoM7OANMxWZ2TRA7gBqKjBspvgar3QFnfOwAna/Aoox1MtZpu9NJPwvJagfmRvEVlTF2vPO1q4iTMzAqzXztDv+8Bfw2Jf/mnIE7GDOU+dqVDA/PTRJlMiGDdHAHppJG1jBwC/VkrFO3Mxw7sNIdcBEDt4Cq9KL4+pLtfB3ct6/jiIDNRvEVlbHOqStffI1verbETQ8wJtvZJ7Uqs2+08zWk+oJRNpP5GnaJHWgYY106cM+v/5VmQm4ym4kd8MXXFsXWoP7ilyuZQo1WvL595+s2A7eARfVMfH3JZr5y3QbmR/EVlYms01Y43PnakSWQGxjlHwY6LYwdSM4HvvhC5ivGZDNfO1sM3GqYKNMZRwfNjIgdQM2ZkYFbYbjiTOexzld2TgDz8p2vO93xkhHXbWB2FF9RGWMzna9bvvM1oqENGDXW+dqeh2ffpBWGo51v6zoi1M7owC05to42iM3EDrD+Z5QO3AopvqKWorGBW8FqX64aBm4BVfGdr/kDt7hwA7Oi+IrKWOfUHR24FVg62oBRaedrkvnaooeDQexA/HMyXzEmrdB3BmuE7tfGiKxTN9mWTOf7jOh8Rc2Ndr4GWnGHXDQSO0DnKzC3vMxXX3yl8xWYHcVXVGao8zUpvm4poqMFGOUfllvY+WoKBm5xmkAq293n1wi5r41hrMusfzpfZ+JyMl/JtESNZAfqSfEaX+nyNiOxAy26vwKq1k8zX/MGbnHhBmZF8RWVsVbqBslDwFbS+SpLIDcwynf2pZmv7VkjdmTgViCC+zEi293n1widr41hcjJfWf9TStdGN14fEsUl1MpY5muw4vXtO1+36HwFFpV2vnayna/xVy7bwOwovqIykbXaGokd2A4MHW3AKJd5gM7+vAV88XWs85UTBbxsd59fIzxAN4bJy3xd5wFtEmIHUHORceqE2S65dWW+MnALWFR+56uPHeDKDcyK4isqY5wysQM7kqStwHByBkb5B+gOsQNkR2FMboGJb5CmiKxVZ+TlC/cJU2LgFmouv/N1hQcQJcXXbQZuAYvy9+ydkRxnidsyYB4UX1EZa526Sm5yks7XriwnZ2BUizNf08SFcDTzlRMFEn49BHT3NY1zTtYp0/nqP1/jQW2SvBcTlrWB+oisHct8XW3nq48d8MVXOl+BeUVJ8XX4hQpZ7cC8KL6iMsa6QeZrJnaAjjZghBvpfG1RZ4ZJM1/jn1N8wZihApP/BqHA1ARm7EGO7YszyR24xdpAffSNG5qMHmjFO1t856svvrI+gLnZvM5XdqwAc6P4ispY59SRjR8KkqJSNzB0tAGjiB1I35xTfMGYvK3VXEcawXfRhKOdr+s6oE1D5itqrm+stjojXXKrXOA2Gc5I5iuwsCin+EpWOzA/iq+oTOQ7X8NuOiRlS4azMzCqzbEDbvhGLnM/B8QoMDXWaOdrkG5f5EZhKjYzrJG1gRqKi6+Zyejhil+upi+3t4d/DmBmxtH5ClSJ4isqE2e+2pHiq+XkDIzyD8tp52t71kga3h8MF184TyDF1urGGn2QI3ZkRrlrg+IS6qMXDRdfA60489UaSUEm1onOV2BexvgXppk1zUtTYG4UX1EZ42MHssXXwPBQBYyymQdoqVUPz7Zo2zHnCXh0vjbW4EEuefmSxo6s7ZA2S7o2QtYGamks83XFqQOyUXztSJ5DKL4C8xtEBQ0+474dmB/FV1TGWKeOTHzTk7xx3mLgFjDOmbjwGrbv4Xm0843iC8b49RB05DOBuctvhtH8uHSeGn+/08l2vob+5V17rh+ov7zM15Ve39P7q6T4yvoA5ua71rOdr2HAfTswL4qvqIyxTt1guPO1G1gGbgGjrBk8OAdhqx4O/M2af3NO8QVjcjtf+f5ogkHmc/z3OsiOW9cRbRjWBmrMWqfIuuHYgWDF13drhjOR6XwF5pY3cMv/iLgwYHYUX1GZyPrYgU4m8zXiuQAY5ewgciAIWzUQIo0dCEY739Z1RKidtLsvyHyDtOcFRZNFIwO3/HmAyZxTcgzcQn31bfy9ODRwKwhWe333L7fT2IH23F8BVTPJmh4euOUzX9dySMBGo/iKyhjr1FXyxjmJHegGlo42YJSzgwfnoNOqh2cz8hbdF1/okEcqGztAgalRfOZrOBI7QOfrlLJ54ekfHsUl1EM/Wd/bQ8XXFXfIOV98TV5w0/kKzM0kt17doeJr/JXne2B2FF9Rmb6xg8zXtPOVzFdgTItjB3zm62jnK+cJpIa2VtP52iRR0kUz2vnKM9yUhgZukfmKeulHvvM1yHy64sxXG41kvvJyAphXXufroGkCwKwovqIyceerz3xNOl9F5iswxplM52u7iq+2qPOV0wS87FAhv064jjSCHRu4N/w5JshbGy26fqDe+kmb3FZ3uPN19ZmvncHLCTrDgbnlZb6GadME121gVhRfUZk48zWJHUi6+raCiI42YJSzg87XsGWxAxRfMEnSaTE8VKg9a6TJRh/kAjpoZpM7cIu1gXromRpkvjr/HBJKCogdABYw2jAhsWMNWATFV1TGWKeOGy6+hqKjDRhjs52vQasenkczXym+YAzdfY0VmdH1H39OdtyUctcGnX2oh7zM12DVma/WDLpewy6dr8AC0hemQbb46nescd0GZkXxFZVwzsXFV5/5mjwUhGLgFjDGZR4OgrBVDwe++LIVxucIii8Yk821FJmvTeKLMGS+zsmvjc7WYPcEawM10S/qfF3lQWQz9cMOna/AAtKGiU5O5ivXbWBmFF9RCX9yDn3ma1J87QSOkzMwymZiB4J2xQ74gTv+Ro6bOIwZfTkh8Q3SEGOxA8nnxI5MyReShmIH+LNDPfRyBm6tvPPVZYuv3VbdXwFV88/33WzsQPKV6zYwO4qvqET6QOUzX9POV8fJGRg1Wlxq0cNBP+18pfiCAtnOJQpMjTIaO8LLlxmlxdcukRyonfyBWyvOfLVR5v6KzldgEf75PgzofAWqQPEVlUg7X91I8TVwZDkCo5wd7LcPwlZl9kXJw1m3Mxo7sK4jQu3kdr5SYGqC8czn+HNevkzJF5KCTuYPrz3XD9RbbTJfw27847DD+gAWYPM6X7luA3Oj+IpKDDpfbfywTOcrUGw0k6xFhSWmnWOioVgOMl+bZLCFkZcvcxnqfCXzFfVSmPm60s5Xk+SFi8xXYEGj9+xS5rq9jgMCNhzFV1TCd7OFo7EDgePsDIwaix1ozyLxN3I+E46BWxgztD4ovjbJ4EEu/nm6fZEbhekkmdnEDqCOeqYmma9BJvOV4iswN2OdwmDQKCFlYwe4bgOzoviKSozHDiR5bo7OV2DMUKZl0KptcWnsQOhf0JAdhRHZziVfYKI41wiDgTzDna+Wv97p5A7coviKeuhH452vgdbR+epjBxi4BSzCOJfer3tct4H5UXxFJdJuFpe56QlCdQLLIzMwytnWDtyKRvKjGLiFMWS+NtZBP37RdGQr/vvl5cuMcgduteflHeotzXwdGri14g45Gw0PbKTzFZibsW4ockDiug0sguIrKuE7XwM3PKU6znxd44EBdeTs4ME5aFnmq4m3MIWj087XeVCoFzt8HZHUqjXSZL74upsUX3n5MqPc4itrA/VQlPm60ucAZ4c7X1u0swioWmTyiq/xV67bwOwovqISURo7EA11voaBIxMGGDW6rbpFD899a9UdmYQscROHjGznq8h8bZKDZFvyzpaPHeDly0x8ISnsDF5QcO5ETdQi89WawYsJBm4BC7FuvPjq78u4bwdmR/EVlTDJEIhwJHYglOO5ABg1NnCrPZ0Zxjht5U1N5TwBz9qczle+QZrgcCR2gIF7M/KFpIDMV9SP73zdHnrBGqz25Uo2doCBW8BCImvTmDBvrBYLYGrddR8AmiHtfFVmu4+CuPhKTwswzGWKS2HLYgdG8qMCMTUVI1ymc4kCU6Ps94ZjB8iOm5FfG9kBKKwN1ETewK2VZ75mm0Badn8FVM1Yl8aEeX7HCp2vwOzofEUlIpPNfM12vlpZ7nuAYXakuNSiG5i+sWMPZlKr/ggwSW7mK98gTXAQGXXCID0HkPk6I5uJdpKSgULt2TmBevMDt7a6w9FCK818tVFmZxGxA8AijHWFna9ctoHZUXxFJcxQ5mtm4FYgOl+BUc5mHg6CVj08G+vUHcqD82/Q13VEqJ2hWA4yX5vkoG+12x0exiPxEDe1seIrnX2oj7zM1zAIVtv5ahm4BVQlsi69Tnsh9+3A3Ci+ohI+diDufB0UXwPnODkDo4Y6+9r18Nw3Tt0wp/OVlzTwhtaHv+nn+6MJDvpGR7Y7gw8YuDcba8Y7X1t0/UC9+czXrXD4BctKnwNcZqApA7eAhYw2TGRx3QZmR/EVlYiSG64g+2AQBAoDBm4BY5wdiR1oz8NzZC2dryg31BlO5muT7PeNdrqD4iuDO2aUHSYkte76gXrrm3g4z2hG5EqLNNnYgbDL+gAWYEbmNEgarG/u24GZUXxFJUza+RqNZb4ySAcYMTpQyLVnW1yUkx8VBGLfMQZspnOJ4mujHPatdreGJ6FLdNBMLVtYkii+olb6xg1lukvJFuWVZr4Oz56g8xWYn7FOnbHYgfgr121gdhRfUYmi2IEOm4mBcdlt1S2bxhsZOxQ7IMU7j+l8RWoo85Xia5Mc9I12t8Y7X3mGm9Jo7EDLrh+ot15kh/JepXiNr7RIk30OCbsUX4EF5HW+BmLHGjAviq+oRNr5OvLGOQgcb8aAUaPFpRY9PEdmPD8qDAJe02Ag+3JCDNxqkoPI6Eim+MpD3IzGMl8D1gZqo2+strsjL1eDFa/v7Bph4BawkLzMV2Y1APOj+IpKRIWxA2S+AmOsHeoQl23Pw3NknbqdNT+cod5yO1/5BmmC/d5w52vAQ9xsyHxFjfWNzY0dWOn6tplYJwZuAQuJcmIHBoMyV388wKaj+IpKGGsVyCpwdizzlc5XYETbB27lbGHiNIGUHY6vkdSqNdJkB2OZr/FX1v+UbDTS+RrS2YfayMt8DYJgxZ2v0XDsANcOYG7W5Qzc4sINzI3iKyoRWaeOkhuczENzSDcLMG5s4FZ7Hg76Jn/gFoP5kHKWzNeGOohGM1/jcwHrf0pjxVcyX1EfPTOe+bry67tj4BZQlci4sTkNYUBcEDAviq+ohBkqvg7HDtD5CowY7exz7elcinK2Ja56GDJqzhrJ3+zTYdEoh307HDuQfOUhbkrEDqDG+lFe7MCKT982E1tD5iuwEGOdRmqvmes2F25gVhRfUYnIZIqvacdSQOYrkCebadmyadV5k1PDIKDzDQN5ma+U5xvhoG+GYgcGna/rOqINMzSMThRfUSt5A7fCIFhtkSa7Rsh8BRZiXHHnK9dtYHYUX1EJY526St4uk/kKlGtx5mucCTea+UrnGzKGOsN952t71kiT7feNdrvjA7e4T5hSdku11LrrB+otN/NVK76+OzOc+UrnKzC3yDqFYdHALa7bwKwovqISfWvVySm+BnS+AuOsHY4daNHDQTxwK2caMucJeHmdrxSYNp5zTgd9oyPb2eJr0kGzroPaNHkDt1gbqIn8zNcV5zpnYwfIRAYWYnKG5IakQQFzo/iKSsSdr/kDtzg5AyNGi0stWiSRdep0xt+i8wYdqezLCdH52hR942SdhjJfJQbuzWS0+BpSfEV99HMy3Ve+RTm7RoKA9QEswFjlRoVJkuO1KTAziq+oRJz5mhM7EFhOzsCooYFC7Xp4jozTVsGNHCApeTmRWR9Sq15QNNVBFN8j7ORkQvLXOyVL7ADqK6/4utJoEeeGYwdYH8BCjLXqBKPd7PFX4sKA2VF8RSWMdeoGvvM1m/nqODkDo5wd6Xxtz8NBZKy6OQ9ndL4iZUcenqVWrZGmOujFxdfRzteQ9T89G2WG0Kl11w/Um7HjL1PDVRZq3OjgX9YHsIi83WoM3ALmR/EVlYhsfudrnPnK2RkYMtrZ59qU+To+cIvONwwh87WRDvrx3+GR0dgBBbyknVZe5muLMsNRb9a6sXzIYJVblP1ayA5s5NoBzC1/TSf/jBt3YGYUX1EJY626Gr3pCRXK8lAFjMp29oXtGggRWTeWHxVPQ+ZEgYTNvpwg87UpfOxAbuYr8UTTGYsdaNf1A/UWWVucD7mSztfx5xDG+QHzi6wbjx3QiofoAQ1C8RWViDtfR2MHgnjg1voOC6inFscO9I1VNxyNHQg4T2BgNLNPatUaaaqDvi++jseO8Aw3JTJfUWPWSeE6u+RsFH/N7MBjfQDzszkNE/6nXLeB2VF8RSWMddoKk7MwsQNAOWeHi0st2jZqcmIHmHaOIc6Nxw5g4x1GcRFkpzua+Rqw/qdlo8G1Q0qKS/zZoR6MdRq5vK+2UOPvpVr6chuoWmSdumP37PHP2dkKzI6nGlQisk7b6cCtQdZSKMdzATDKmkE7SNBp1cNzZJw64ei081b9EWASa6Qwk4ks8QDdACZ5UhtZ/knsyOqPZyONZb4GrcoMR70Zm3d994WaFSxyN/ocwssJYBHGupIheqwtYFYUX1EJY512wtHYgbjzlZMzMGJ0oFCLCkt9a8c7XxVwnsDA0Pog87UpbFJhHc2PY+DeDEaLry3LDEe9xcXX/H+2khcsaexAO++vgKoZVzZED8CsKL6iEn1jtRWOv3EO6HwFxmUHbrWoc8na+HwwmvlK5yuGZNeHKL42hUkW+Wh+nAI6aKY2tDZEcQm1YlxePqQ/h6/gAMZiBwLWB7AAk7NbTSIuDJgXxVdUwlinnWC88zWU5aEKGJUduNWizqW+jf878/Kj2HaM1GhnuER1vgH8Gg9yOl8xJUfxFfVVNpyHgVvA5okKutnZsQLMh+IrKhFZp61gfOBWyKYEYJhzktygqNSih4PIxOeD8S1MkuNcAc+ODKSTWrNGmiyNHchZ/7ykndJY5mu7Bjai3iLrxmJFgpVmviZrgdgBoBJxN/t4uSjkug3MheIrKmGM03Ze5qsj8xUYYnMeDlry8BwlxZfuyGv0gNgBZOV2vvIAvekMma+LGyu+tmfnBOrPWqewoPN1JUt8LHaA4iuwiKIc53hWw+qPB9h0FF9Richmi6+Dm54wsDxUAVm+MyPtfG3Pw3NkktiB0c43BWRHYcAayXdaMHCrMfyL2NGUgUB00Ewtr/OVPzvURNlwntXEDtD5ClTFOZcUXwsyX9mxBsyM4isqYazV9ljma0DnKzAq9+GgHWtk0Pk63hnTjj8BTCWv85XvkI1nCwZuBUHA3+60rBkpvjJQCPUR5XS+pu/PVrHIiR0AKuM7W0dfqEjsWAPmRfEVlYgzX3NiB2R5qAKy/IPAUOZru2IHtsLR2AG2LyEjO9Gd2IHGSBrfczNf6Xyfko0yLyTUqusH6s/mZL76gXorWeJ5sQMr+82BZomSIbmj12zJxwWxroBZUXxFJUx24FbmpieU454HyHIjDwdhezozfOwAxReUys185ftj05nk7zAcK87w1zu13NiBdlw/UH/xcJ78zNfVxA5EyW86aAKRxBoB5mAKhmRK8XWcpglgdhRfUYnIOm3lDdySo6gCZLU4k6xv8mMHAlF8QcKOZIeLzNemcGnxdfjzeHAHJ4CpjMYOhO3JDEe9WRs3W4y9XNUKM1/HYge4fgDz8sXX3NgBkdUOzIPiKyoRGZuJHch2vlrejAFZaexApvhq27Ft1G9h2hoZnRoGAcH9iI12hvPw3BhFXTR0vk7JWkmOzlfUku9sH40dWGnm6+jLbV7eAXPz1+zR3SoSma/AvCi+ohLFma+OogqQ5R8C0mnu7elcikzRwJ1BwyNaLn149usjkMRdfhMUPciR+TyldEt1Z/AZxVfURLq+x16ukPkKbCJTMCRXitc5O1uB2VF8RSXizFf/0Dw8cIuiCpCRPhxkB261Y5GkA7c64w9nvKSBpPHOV6lVa6TJ/HNa3jR01v8URvMspWTnBGsD6+e3II9uUQ5Wmfk6FjtA5iswr7LM1zh2YMUHBDQAxVdUIsoO3MoUX0PeigHDxrZVh5JcKzoz/MCtbjh+6eEmDpJyto2K4mtDlG1LbsHpb3F0vqLGosJYkaTzdRUHwcAtoDLpms6JHaBpApgPxVdUYrjzdZDVF8gSyA1ktfjhICoI7w+DgOILYrmdr0Er1kfTDbYlD38er39OABMVdb6yNlADtjBWJPnnq1jjhbEDrBFgVqWdrwFNE8A8KL6iEpF16hZlvnJyBgZM8gDd2Yq/hu15OPCZr92RgVtx5xsnCmiwhXq0u48Oi41nizpfxUPcVNzIPZZE8RW1UVSoCdLM11XEDow/hwx9DmBqZZmvAU0TwFwovqISxlptafymJ2TgFjDM9OKvvvjaooeDflJYG72Ri7cvAcp0vmZuTygwNUJRZxzrf0qFsQNmPccDZBQVX/1PVzNwy6+RTKa+xPUDmENUcM2OP6NpApgHxVdUIjJOHeUM3HKWjhYgy/bjr+FI8dU2/wHamPzYgXj7EicKqCTzle+PTWcKBm6J9T+dvNiBsENhCbWQZjoXZL6u5FmgMHaA8wswq8EQvfFyUaCA6zYwB4qvqIR12diBwU0PsQPAiNHYAf+Q0IIHaP9wNp4Jx/YlJPIyX0XmaxPYsoE8rP/JyHxFjZmC4Tz+Z6vJfB3N1Pdtt6wRYFY+KqyTUy0KGZQJzIXiKyphrFPHxw4Eg+0+gSzbEoCstPO1fZlkRcWXOPOR8wRE52uD2fTly/DnrP8pjXb1SRRfURs+rrso83Ula9yNDv5tz/0VULVBlEhO52sQsLMVmAPFV1TCOsXF17A7eNOsIMl8BZAySfF1LPO1+bEDPj9qNHYgZ5Aq2iqv8zWg87UJijrfw4Dti1Mpyny1rA2sX5R8H64389U3gVB8BRZlXP49u8SgXGBeFF9RCWOduoEZ2w4XZ75ycgZSo5mv/kG6Besk7XzL6YzhPAFJg4fnsc5XHp43XWHnO9sXp2NHcvUl1gZqo+j67l+2rHbgFsVXYFEmuR8by2kXgzKBeVF8RSWMdeq4nOKreKgChoxlvrbn4aAsE47zBCRlOl8ztyd0vjaC8XX1nMxnti9OgcxX1Jhf32PX9+SnxA4Am8Wv6aLOV5omgNlRfEUl4oFbZqRbKVAgOl+BIaYXf02Lr/7JpPmxA6Zk4A7nCUgqyXzl4XnTFWW+xj9n/U9E8RU1Vhw7kHS+ruIgRrvDKb4Ccyta01LS+cplG5gZxVdUIh24Ndb56nimArJGYwd8NlkLHg6Kiq9i2zG83MzXUFxINp91TmEwGMDjxR00azqoTVIYO9D8F3eov+KBW8k/X8VF3r+gSDNffeBs8++vgKoV3rOLzldgXhRfUQnrCmIHyHwFhrU5dsAVdb5SWkOCztfGMtaVdNBwBpioaOAWawM1MLi+D38epJmvq4gdGMkMb9H9FVC10uKraJoA5kHxFZUo63zl3AxkpJ2vo9vimt+9VDhwRxRfkCjqfOXheeNZN971KsUPcXS+TiGv+Bp2WBuohUGhZvjR0l/u1zpwC8DM/JrOy3yNB25x4QZmxVUJlYiLr6OZryGZr8AokxRffedr2J7Ygahg4FYY8gYdCTvSuSSJXIpmsM6NrX0pLsjytzuFwsxX/vSwfkUDNX3m60pesKSZ+tvxVzpfgbn5e/bRIZn+M8uyAmZG8RWVsE5x8XWkWylwjucCIGss87U9Dwf+4SzM6XzlJQ0klWyt5vtj0xXFDgTBirYkb7rCzNfmXztQf4Pr+/DnfsWv5Bqfvtz2xVcyX4F5+d1q3Q6Zr0BVKL6iEsWxA5ZnZiBrtPPVF19b8ArZ36iNbmEKyHyFN9q5JCXfIM1fH01nrFNOAw1Tk6cVHcRfu7uDz4JgUJQF1shf30c7XweZrys4CFMU68T1A5hVVBI7wI4VYD4UX1EJ45zCvIFbsmTCAFlFxdcWPBxERZmvQUDmI2J2pHNJoruvIZwr6HwVHTRTyS2+kvmKeogKuuQGma+r6HztxbuKfAG4RfdXQNVMSexAPHCL6zYwK4qvqIRNM1+zxddAgXMUVYCsFscO2IIbuZCxqfBGO5ckOl8bwhRkvtL5OqXoMP7a3Rl8xosJ1ETR9T1Ydebr6Is7iTUCzGEwcGu8XMSsBmA+FF9RCeOKB27xZgzIMEmm5Vjna/O3jprk+WcsdkBMO0diNLNPStYI3yCbztjxvGdJEtlx08ntfA1bce1A/ZmCnS1p5+sqzuE2GtxbSRRfgQUU5ThLycAtrtvAzCi+YmEuGaqVGztA5yswzPYlBYMXFf5rCx4OTJJrO1qACYOAeBLEcjNf6e5rAuec8mqvIZnP0ynsfOVPD+tnXHGskETnK7BpopLOV5omgPlQfMXC0jdjBQO3JHJhgJTp53dmtGBoiinKfAxaMW8M00g7X5no3jTG5scOBAq4R5hGUeerHAVYrF1R56tf8ivpkjM9Ol+BihS9UJEYuAXMi+IrFpaenAs6XyWeC4CUjQZ5r9Lg4aAFtzHGjk9ClriJQ0bewC2R+doExrnc2AGy46ZU1Pkq8QeItUuLr2OZ7mnuwAoOouDlNusDmJlJssLyiq9hQGMVMA+Kr1iY71iLYwfGM1+lNpSVgCm1uDPDWFs47ZybOEgqiR3g+2PTWesKpiaTHTeV6EDq7AxaCaXBj1tw/UC92YIuuXClna/9kWsH6wOYl0mWbFHnK9dtYHYUX7Ew3/kaKsopvjpJjhM04LW4M8PYojfoTDtHwscOhKOxA3yDbDrrih7ieEE7lehwOHJAyhRi+RPEekWmIHZAK858zdtZRPEVmJmf0zA6JFfyna+rPiJg81F8xcJ8YTVv4JYkBXKcoAHP9kceDtrTmWELBu4ETDuHZ3JiBwJiB5rAFK7/gMEd04gOhiMHJIpLqI20ESPIz3xdye6WwpfbrA9gVlFBjrPEjhVgXhRfsTBbMnAr/pzOVyBlovFhQlIrHg6Mdep2xi87IZmv8ApjB5q/PpquKHYgjHNHVn9Amya387U91w/Umy0o1Pg1v7LO19G8cIn1AcyhaE1LyTtxLtvAzCi+YmE+ZH888zU+WYeUVYCB0c7XFj0cRAXFF9H5Ci/tfB3pDm/B+mg661xh5jOdr1Og8xU15jtfR7cor7Tz1UbjL+4k1gcwh6hgiJ5EXBgwL4qvWJiZEDsQylJYAbwWZ75a65TT+BqXn5v/n49p2H58HRkaKhSKb5DNZ+z4lmTJd77z9zsRna+osbQRo6DzdSUr3PQKdhZxfgFmZaxTEIyvaYm4MGBeFF+xsCSPO6f4Gp+syXwFMmzU2oEQxjl1Q2IHUGJs26iIHWiIws7XYHAfgRJ0vqLGTEGXnF/yKynUjF4/WB/A3Ix1ucO2JO7bgXlRfMXCBp2vo4OEyHwFxpheawdCGOuUU3vlDToGzGgshyi+NoSxxQO3WP1TyOt8bVFsDeotLb528mMHVpP52qf4ClTE2PwXphL37cC8KL5iYWkgt+1J3fGbHjYUAhktnsZrrCM7CuVG14ckiczXJrDO5W9f1IryIDddaecrf35Yr6LO18DHDqyk87W9sU5A1aKCe3YpXtdktQOzo/iKhaU5T7YvdTIPBpnOV56bgUTLYweKB+5wFweVxA7w/bHprCt++cL6n0Jp5it/flgvvwtu9BqfZr6upPO119r7K6BqZZ2vYfzWdLUHBDQAxVcsLL3hMofDXRlp56ul9xXwTL+1AyGMKcp8pPMVidH1IVF8bYg4diCn+Mpf73RyO1+JHUA9+F1wo2t8tZmvo7EDrA9gXqWxA1pRlAjQMBRfsbD4hssptL3c4muc+bqeYwNqx+ZnI7fh4cC4/OJLELDtGAnbz+l8JXagCaxTfuaz6HydSmnnK+sD6xUlN/qjA3qCJJd4NZmv7c3UB6oWWadO3kVbfuAW121gVhRfsTDjnLoyCuSKYwd4sAJiJhp5OGhPZ4a1Tt1O3rZjcQuH2Oi2UYnia0PYgi6agPU/ndLMV9YH1ivtfB0tvvpbnFU8B9j2ZuoDVbPWjb1M8YIgkGVZATOj+IqFGeu0rSj+yVDna3zCpvMVyGhxZ0ZReD+db0jlDdwKQlGe23zFne/Ejkwlt/O1PS/vUG9Fme6+GLuazNfR2IH23F8BVYvKYgcCZjUA86D4ioVZK+2oF/+EzFeg3FjsQHsenoumnZP5iNTow7OUZL42f300nS3KfCV2ZDplna/cY2HNjB0ftiVJ/pPVZL629+U2UDVb8EJFGmQ5A5gNxVcszLhM52vOG+c4dmANBwbU0VjsQHsenk1B56sU0B2P2OjDs0TxtSGsKy7OsP4ncE4yZL6ivoy1udd3/8Jl6UvcueT6QecrUIWoJHYgDNixBsyD4isWZqzTdtCPf5J9MKD4CoyzfSnMTHNv0cNB0Ram+CNOElBx7EAL1kfTmcLOVwZ3TBQdxl/JfEVNFXW++o+WXqixJvkN6XwFqmCszd2tJvnYgRUfENAAFF+xMOucduSLr3mdr5a3Y4A3Wlxq0cNB2cAdbuIgKRmYMhI7IAZuNYF1Ln+rYiAGd0wSHcRf6XxFTZWt7/ifL/kATBJ/lnt/xQ0GMCszYeAWcUHA7Ci+YmHGOu2ksQM5ma8BPS1AaizztT0Pz4UDObiJg2d6w+tDSjpf+f7YdEX5cXndsBgxsfOV9YH1iqxVtzP+WJmu72V/j6bF12wTSHsy9YGqmbKBW+KyA8yD4isWZq3TtspjByxtbUCsKPO1BXcxRTdyZD4iVRg7wDfIpjM2f+BevP75+y1F5ytqztj8Fyn+s+V3vibPIZ2cgaa0gAAzK4oKk3xcEIBZUXzFwoYGbhXEDgBItHgab9HALbYvIWVyYgcCYgeawLri4gzLf4KizleP9YE1i2OFxj/3K375ma95xdf23F8BVSvrfA0DXpoC86D4ioUZ67QT+O0+47EDoRwnaECKu/fGYgfasy2usPMtoLERidzOV4qvTRC/fBn/POAhbrKJna/8+WG9jHPqhsWxA0v/Fs2NHaD4CsxrUuYr121gdhRfsTA71PmaLb7GJ+xAjucCQBpM421pZ4Z1+Tdygdi+hMRoZ7iUrBG+QzaddUUvX1j/E03MfG3+9QP1Fr9cHf/cf4suvVCTxg5QfAWqEFlXmMlO0wQwH4qvWJi1ymS+0vkKFPLb4sLu4LMWPRxEBZ2vbF9CyubFDoStWB9NZwtjR0TsyCR5k9ylVl0/UG+FsULJ15V1vrb0/gqomrVO3bztKiIuCJgXxVcszDinHRW/cQ5l6WoBpPyBEGpP7EB58WUNB4T6MSOxHBLF14YwLr+LJmT9T2aT3UV5a0NifWDtTEFnexo7sOwnATpfgUqVdr6KpglgHhRfsTBrnbaDvNiBQecrXS2AJjwcNH+NmILYgXhqavP/+zGFvNgBkfnaBNYpP3ZAZMdNlLdrQqK4hNowpvj6LsXrf7kHQPEVqFJZ5iudr8B8KL5iYca5TOxAZhjEUPF1DQcG1E06NGX8JUUbHg6Mye+MUbCCBzNsBlMUO8A3yKYrmoYeBiT6TuTzwseKr+3ZOYF6K+ps9x8tP/M1J5qjRS+3gaoZ69TJC3IWgzKBeVF8xcKMzRRfc944B7IUVgBJMsnQlE5Li68uP3YgDKi+QHGAuDP5uZYtWB9NV1ycCWS5SSjnYwc6BZ2vnECxZvHLleLi68oyX1s60BSomil4YSoxKBOYF8VXLMxmM1+HJvHGd1yhHFuKAUmKkoeDtna+WqmTE95PdhQkDbZW5xZf+f7YdKYgP453L1Mwk2IH+BPEepXFCkkrGKqXGztAZzgwr3hN55eKQgZlAnOh+IqFGSvt+MzX3IFbTpb7HmBC7EDzb2KMtYWdr83/r8dEaedSXuwAF5FN55zyO+NEdtxEhQO3KC6hHozNjxXynyy9uT3v5V2LXm4DVTMF3eySjx1Y8QEBDUDxFQuzSeyA6+wMHgSkTOwAna+ApExxKVt8bc/Dc9GNHNlRkJTp7hstMKkV66Pp4s7X8c/poJlCWnztDH9OcQk1YWxJrJBWGTvAwC2gCpG1hcXXeOAW121gVgsXX4MguDcIgl8PguCjQRA8HgTBX6niwLA5TBI74Ma6leITdsDALSAWJZmvLY0dsEWdb0xNhZTZNpoTO8ALvI1nXEFnHB00k6XF16LYgeZfP1Bv0YTM1+UP3Mp5ecf6AOZmbf49uxQXX7luA7PrTv5XJookfYdz7v1BEJyQ9L4gCN7unPtoBb82NkA6cGso71WZ2AFLYQWQWl98LXqL7j9xzinI6ZxBSxA70GiuZOAeu2MmSAdu5b2YEOsDa2es05GtztjnwcoyX/31I/Noy/oA5hZZm5vj7LFjDZjdwp2vzrkXnHPvT358TdLHJN296K+LzWGd07aiOHYgK5v5ygkakExSfG3ptjhrlTtwZ2XbElFvedOqJYqvDVGYH0fn62RFA7fUntga1FtkyrYor2DvQn8//rp1NPMh6wOYV1GOs5Tct3PdBmZWaeZrEAQPSPpcSe/J+WffFgTBo0EQPPrKK69U+dtizYx12g76+d1KksKAnhZAUmbg1u7gszZlvjqnTs5VZ2XbElFvRd19ClqxPprMOSfrlNvZTnbcFKyJvxbGDvDnh/WKrNNWp2yL8pK/R/391daRwWesD2BuxrrCzldmNQDzqaz4GgTBcUk/LemvOuf2Rv+5c+4HnXNvcc695dZbb63qt0UNGBtnvg4VlKShgVucoAFJUdLZ183pfG34KwrnXNL5Nn7Z8fd2zf4TwESlsQN8d2wy39maHzvAX+9EtqDztUU7J1BvkVnzZHTf+dql+ApUIbIud7eatKJudqCBKim+BkGwpbjw+p+ccz9Txa+JzeFjB4YKShKZr8CoNHagfZmvZcUX3w3HS5qW88XXkNiBpvFrO7fzXSvoitt0DNxCzUXWqpu3wBVf45e+xvs342sHma9AJco6X1fSzQ400MLF1yB+av43kj7mnPuBxQ8Jm8ZYTRi45dhSCEiZgVvZ2IF2PBwYW1J88Z2vnCbazZQMFeKbY6P59Z8fO0AHzUQTB27xJ4j1ikoLNVr+Iu/vj+S9qlWxTkDVjHXqFESJkNUOzKeKztcvkfQnJb0tCIIPJv/7hgp+XWwI65x2gr6CgtiBkDnGQCwtvuYN3Gr2Khl0vo1fdgIxcAsqiR0g83XTDdZ/3sCtgLU/iaHzFfUWGaduzvVdWlGXXH9/OO9VSoqvXD+AeRjrcnerSQzcAuY1OjZ1Zs6531I6ThJtZKxLOl/zYwcCWVlejwGtjh2ISjpfB5mvnCdaLS2+5nX38b2xySZlvkpxLnReZywUd74GnUEnn+d/2vDrB+ovsrZ4OI9WlPk6WnyViK0B5jSpm53YAWB2lQ3cQnvFA7ciBWOxA/EJm85XIBEdSgqGi0st2Rbntx3nhff7j3hH03KFW6vpXNp06frPeZDzne+s/xK2P971KrVmYCPqz1inbsEW5XAV3e39mxRfgYpYW7xbTSKrHZgXxVcszDqnroyCvCEpiouvnKABxcXX7k5O91LzHw78jVzeW/RB7ADniVYrjB1o/vpoOpu+fBn/Z9nOVxSwZvylhNSanROov74p7pILVtElR+crUJmy3WoSWe3AvCi+YmHGOm0FOQ8GafHVcoYGpLi41NkZ/7wFDweDG7nizldOEy3ni695L/Iavj6azpRkvtL5PgXTl8LO+OcUX1ETcedrQZdcECz/5UrewC2J6wcwh7I5DZLIagfmRPEVCzPOqaso/4FZUkDsABCLDuLO11EteDjwN3K5246T6kvD/wgwiSmIHWBgysZL139u7Eiy/rlTKGaj8tgB1gfWrG+KM19X0iUX0fkKVCUq2a0msWMFmBfFVyzMOWlLRurkT+EldgBIRL384msLikum5EaOgVuQVD5wi2vIRrPJ6a0s85m/4hI25wW3RPEVtTEp83UlsQPd3fHPuX4AMzOmuGFCGlzL2bECzIbiKxZmbJz5WtT5Gspx3wNIkjks6Xxt9iIpHbiVfOUmruXIfG2sQezA+D/z54SGnwIXQ+crasw5p8i64uE8wQqu7/2bxA4AFfHX7MIc5+QrzVXAbCi+YmHTZL5ycgYUD9xqaearKcl89W/W2b7UctbHDuQUX+Wozm0wO9XLF/5+C9lofHeRpPRPjz87rJG/vm8VDtxaQT5k4cCt5u8sAqoWJdtV8u7Zpex9+8oOCWgEiq9YmE0zX/NjB8h8BRLRodTdHv+8DZ2vZQN3kq90vrZcOnBr9FpCgWnTlWW+pp2vKz2iDWP6Ezpf+dPD+qQDNQtjB1bwcrV/QOcrUJGyhgkpOyiTaw8wC4qvWNggdiD/gTmOHeDkDMSxA0WZZM1+OCi7kWPgDiSVxw5Iojy3ucrXf/yVh7gShbED/sVEs68fqLco7XwtiB3QkjNfnUtiB+h8BaoQmQnFV9H5CsyD4isWFne+lscOcHIGlMQO5HW+Nv/hIC2+MHAHRYyPHRi9llBg2nRp52vZyxfWfzGbk6svkfmKWojMhC3KwZLXt+lLzkhbBS+3eXEHzCR9oVLSzS7RNAHMiuIrFmZNpFAuZ+BW0vkaOLYTA1ISO9DuzNe84gsDdyAp7nwNQinsDH9OgWnj+XuA3JcvyVd2yJSw/fF1IbE2UAuTCjVBECz3OaB/M/5K7ABQCZNkvnZLhuhJxIUBs6L4isWl3Uolma88VAEUX5U/OZWBO5AUF1/zOsNF5+umS1++5NRmQjrfJ7PReEe4RPEVtTDYolxcqFnqc0B0EH/NjR1o/v0VULW+Kb5nl7JNE1y4gVlQfMXiXFJ8Het8HRRfeTMGKM587bS0+Fqy7ZiBO5CUFJgKBtJJVOc2WFnnu48d4OVLicKBW7yYwPr5yejdwi3KwXKv73S+ApXyL1S6naIXKv66vbJDAhqB4isWV5jT5zNfnSirAJKiXms7X21J5qtvbLTcxbWb6U2Y6N7sNdJkZduSB9lxKGRzhppKDKNDLUQTu+SW/HKlvx9/LRxoyvoAZjHphQpxQcB8KL5icbYffx19MMgUX6mpAIq3xuUWX9szcCvv4SzMK8iifYpiByi+bjw/kCc3P47O18lsxIsJ1JZ/uVLWJbfczNek+Jrb+dr8+yugalHJPbtEXBAwL4qvWFjgi6+Fna+WkzMgJcWlgs7XhnculW47Tr5SfGk5UxQ7wNbqTTcozhR3vjb8FLgYWxQ7QPEV65d2yRUUapae+ZrGDpD5ClShX/bCVIN7ee7bgdlQfMXCAjNN5isnZyAeuFXQ2dfwNeIzXzt5na9EekJKXk5QYGqiwbbk8dvOQGTHTTRx4BZ/eFifybEDwXK/Rft+4BaZr0AVTMkLUynbNLGiAwIaguIrFha4SZ2vjoYWwLl44FZuJlnzt8X5G7m84uug+MKZotUmxQ5gY/VL8uMGma+s/0ImksLO+Oe8mEANlHW2S3GhZrmZr77ztSjzlfUBzGLSC5UgHZTLdRuYBU80WNig83U08zU+McexA5yc0XKm4CWF1IqHA1MycCvdVb7KA0L9TOzua/YaaTKTPMht5XW++oF7nACK2Wh8d5FEJAdqwdgJW5SX3flqC3bgSa24vwKqNhiSWZTjHH/l8R6YDcVXLM4lNz1lna+cnNF2LX84KO189W/QOVG0m+lRYGoonwlZtv4t1ddiRZmvYm1g/foTu+SW3PlqTfy1qDuc9QHMxA/JzLtmS4NBudy2A7Oh+IqFhUVFJTJfgQFb0CEuteLhwJZkvqbzdjhNtJvp58cOUGDaeL44s5UbO5D/cIcMayYM3OLkifUZ5EMWdckFy+1sT++vKL4CVejb4mu2NIgL4vkemA3FVywssMl26rHYAd/5ankuAFpefI1KOl/TN+grPSLUjukzVKih0mnoOcWZweAO/n4L2YhhdKit/sQuuSXvbHFJ52tQVHzl3ALMYlKUCLMagPlQfMXCAl9UGn0wyMQOcHJG67V8W5zvjMnrcgt4gw4pGbhF5msTlQ3vCKmtT2YKYgdYG6gBM7FLLljuy9X0/qogmoP1AczE71YpeqFC5iswH4qvWFiYdr6WZL6u+JiA2ml556svrOYWX7iJgxTnWubFDlBg2nhl09DpoJlC4cAt1gbWb1KhJlx65mtZ7ADFV2BWURoVVDxET+K+HZgVxVcsLJgwcCuQY5AOUFZ8VdD4O5io9OGM4gtUEjtA5uum88M78rYwpn+9qzygTWMjOl9RW2bCZHQtO/PVf/8Xvtzm7ALMwpQMyZTYsQbMi+IrFhYUFZXIfAUGJna+NnuR+Bu0kM5XFDG98u4+ynMbKyrZlhykHTT8/RayUXFXn8TJE2sVTSjULD3z1d9fBTmPtS3YWQRUrWxIpsSsBmBeFF+xsEHma3HswFLfeAOboCyTrAXb4pLGN3VyM1/ZvgQlna/EDjRRWec7L1+mYKPyPGQegbFG6RblguE8YRAsd32X3l9RfAVmZdKooIKBW3S+AnOh+IqFhWlH32jxNT4zh4Ej9RUozSRr/sNB2RamtPjCeaLdCmMHmMi06frJ+s/bljzIfF3pIW0O54gdQK2lna8FXXKB1pn52vz7K6Bq/pqdN6dBomkCmBfFVywscMnArZyHZheECmR5qAJaPnDLv0XPK74O3qCv8ohQO6aXX3wVma+bzpgpBu7x8iVf2tVHHjLqKY0VKYwdWHLnq0vWSEDxFahCVHLNlrI7VrhuA7Og+IqFFWa+SlIQKpTj1RjQ9uJrcgoojx3gPNFqtih2gALTputP8/KFv958NnnBndfVJ7Xi+oF6Kx+oGa/x5Xa+EjsAVCkquWZL7FgB5kXxFQsLXEHmq5QWXzk5o/Va/nBgSrYl+k84T7QcsQONFRmrbhikL1qy0pcvdL7mK8rV91pw/UC9RVPkQ64m87Vo4BbnFmAWZddsiR0rwLwovmJhoSvIfJXS4isdbWi9lmeSlQ3cCtPPOE+0mukVXkckNX6NNJmxTt2SPEiJ+kihsl0TUiuuH6i3yJTnQ4ZBsNwiTVEmstSKgaZA1aKSa7bEjhVgXhRfsbA0dqCTd+MTkPkKSK2PHfBbDnMbU8h8hR8qlBs7QPF10/WNU7dkErpE8bWQmVB8FcUlrNeg87W4+LrU67sz+XmvUivur4CqRSXXbGmwY2WpcSJAA1F8xcImdb4Gop8NmFx8bfYq8QO38m7mKL5ApnhwI5mvmy+ytrjzNX35wgkg11Sdr/zZYX0Gw3mKYweWnvlKZzhQmbJrtpTdsQZgFhRfsbBB8TWvqBQolCV2ACgtvja/c8l3xuTtShxkvnKeaC3Ti7+WZb7yGm9jRXaKztdVHtAmSQduUVxCPRlrFQRlA7eC5We+MpAOqEzZNVvivh2YF8VXLKxTNgwizXxd7TEBtVM6cKv5/eHWOoWBygfuNPuPAGV8gYnYgUbywzty0flabqqBW/zZYX361hWvb8UvXZfahOEovgJVKr1maxAhxqUHmA3FVywsVCSnoHCQUCDHQxXQ9oFbrvgterqrnPNEe5mS7j6KrxsvMsXDO4gdmWBS5msLrh+oNzNFl9xSM19tROYrUKGya7ZE5iswL4qvWFjHGZmg+KEglG14Tx8whZYP3DLW5Q7bkjLTzld2NKidNHYgp/NVaXV+ZYeDakXWaatT8PIl+crLlwJlL+6kVsTWoN76k7rkgkBumVf40sxX1gcwq7JrtpSNHVjN8QBNQfEVC3HOqeMi2dLiK52vAMVXp05BQH8Y0vnWepPWh8Q3yAaLbHFxhszXCSYO3KK4hPUydnKXnF3mt+ikzFfOLsBMImsLM5yl7MAt1hYwC4qvWIixTl0Z2ZLtcGS+ApqQ+dqS4mvRMI7kKy9pWsyvj9zscN/52uw10mR9U7L+feYrLTT5JhZfKS5hveL1XdIlFyz5+u7MhNgB1gcwi74pz3FOr9ssLWAmFF+xkMg6bam88zWQZTsh0PbM17LiK51vmLQ+pMavkSYzZbEDvra+wuPZKP77nsxX1JSxVlslna8lNZxq2IhYDqBCk7rZfecrL02B2VB8xUJ856ubEDtA7RWt1/bYATdF5xsnivYqXR90vm66vrGFD3KBGNxRyq+NoCg0u/nXD9RbVNLZLsWFmqWu70mxA6wPYCZxjnN5N7vES1NgVhRfsZDIOG0Fk2MHeDGG1ptYfG32IrHWZTKihoXcxWGazFe+QTZWVLKFMSQ6rlxZZI1EcQlrN3E4T7Dk7cmubOAW6wOYVbxbpSR2gJemwFwovmIhkbVx52uYk9MnSUGgMHDLnXIKbIJJnX0NfziIbHHxhcxXDLr7iB1oonjgVlHsgH+IW+URbZCySA6J4hLWbtJwniAIlhs/ZidlvrI+gFlM7mZPfsB1G5gJxVcsJI4diApjB4Ik85WHKrRe2r2U94DQ/OKrtU7hpGnnnCfay5bkWlJ83XhRSX5cmDa+cwLINc3ALU6eWKOyznYpvsYv9VuU2AGgUn1rS7vZ/f08z/fAbCi+YiHxwC0jV/JQ0JHjwQBoeewAma8oxcCtRisrztD5OsGkgVsteHmHeit7uSLFu1uWm/laNnCL4iswK1OyW01ixxowL4qvWIgfuGULYwfIfAUktX7gVmQnF185TbRYaXcfA7c2XTxwqyh2IP7KQ1yBiQO3gsa/vEO9TRrOEwZLvr6T+QpUqm+cOqUDt5Ida6s6IKAhKL5iIVFSfC174xyKzFeg7cVXa506BQO3fHD/UjPhUG/TDNzi22NjlQ3vYODeBAzcQs31jdV22RblIFh+52tp5isnF2AWkbHlA7d4aQrMheIrFmImDtwKFQZkvgKlD9AteHg2JZ2v/uU693AtNml9SI1fI00Wd74XdL4mX3mIK8DALdRcZCbEDgRBGuu9FNaWrA9iOYBZld2zS7w0BeZF8RULiaxTNyjf7hPKUVQBbCQpGFQas1rw8GzLMl9F5mPrpQWmvPVB7MCm6xurLQbuzWeqgVusDaxP37rCWBHJJ2OQ+QpsiokDt+h8BeZC8RULiYyb3Pkqx3ZiwEatnlZdlvnKtHOUxw5QfN10pmQgD9sXJ5g0cIviEtYsKnm5Iq0o87U0doD1AczClAzJlGiaAOZF8RULMdNkvgaUVIDJxddmPxwY6wbblEYMii8rPCDUi5sidoArycbqm+LOOHYvTjDVwK1mXz9Qb5NiB5af+crALaBK/ZIXplLmus1LU2AmFF+xkMhadWVLbnoChXKyVFXQdqUPB81/eLau+C16OjWVm7j2mmrgVrPXSJNF1havfwbulZtm4Bala6xR39qJsQNLfQwoix1Q8++vgKpFxqpbkNMuDeKCeLwHZkPxFQuJjFNHRuoUxQ4E6rCZGGh9JllknMLC4kuM2kuLMXCr0eItjPm3nAzcm2CqgVv84WF9+sZqu7T4Giz3W9SVNYGwPoBZRXS+AktB8RUL8bEDwYSBW2S5ofVKYwea35lhnVOnIHYgHbjDa5r2Ki0wkfm66eLhHQzcm0tZJIfUiusH6i2akA8ZrmLgVmEsR/NfbgNVm7ym/X07gFlQfMVCIuvUkS3tyAgCx0tnYFLma8NvYaYauMPzUXtNFTvQ7DXSZJFh4N7cpokdoLiENSrLdJbiFyzrzXzl3ALMIpoiSkRiUCYwK4qvWIixTt3AKCiMHYg7X9mWgNZr+UCI0oFb4g1666VDhXJe5BE7sNGcc8kWxvKBW3S+Fpg4cKv51w/UW1TS2S4lna/LPICWxzoBVYvs5G52ifcawKwovmIhURI7UFZUCmUpqgAtfzgwrrjzjewoTJf5yvfHJjJJVXWLgXvzofMVNReVZDpL8Rpf6uBdZ/Jf3MW/OesDmIGx8Y7VSWtaovMVmBXFVyzEWKuOjIIOma9AqUmxAw1/ODBWUxRfV3hAqJe0wJTX+Urm6yaLkqJLpzDzNcb6LzBp4BbT3LFmfVPe+RoES17fLd9ZBFSpb+L1UjpwK/nKdRuYDcVXLCTufLXlA7fIfAWmKL42e5EYaxm4hWKlma8UXzdZlHa+5t9ysv4nmDhwq/nXD9RbXHwtfqQMg2DJsQNGKurSo/gKzMTvVplu4BbXHmAWFF+xEGPdxM7XwDmy3IDWd75Ojh3gPNFi0wzc4iZ/I0UTumgYuDeB7wov3Fbd/OsH6sva+B6/rEsuDJa8PdnR+QpUZdD5Wv5CReK6DcyK4isWEhmnLRkFYdHArUBh4MRDM1rPmpLM1+ZvG7VOCgunnfvMx1UeEWplmuJrw9dIU/VNeRfNoIMGuWwkKaCzD7XUT6ovZZ2vQRAst/hqI15OABW50Ytf+B3fKYq6yTZNcOUGZkHxFQuJpsp8tbwZA1re+RpZW1h88Z9yE9diUw3cavYaaap0C2NJcUZi/Rcqy7OUiB3AWkUTXq5Iq8h8ta2+vwKqdP0gfhl+fKegsUqZNKhVHBDQICV3c8BkPvO11ynqfI0HbpEJg9ZrefHV2kGH26iAzjekna95BToyXzdZuoWxqPM15CmulI1Khm0pfgr2Ly+AFUuLr5MyX5dafC1ZI0EoycXV34J7EGBj/MrfkD7wH5f6W7zaOn1gJ9Lxn+9Kv5i/Zu5y0gd2+jr6yx3p1+jlwwTf8Qmpu7Puo6gFiq9YiDFGYeAUlna+MnALKC2+tmBadZz5mv/P0jfonCjaa9LLCYnuvg2VDtwqOAHQ+T6BK+nqk1oRW4P6GsQOlE9GX37ma1nxVRRf0QzPvlfaOio98vuW9lu8dGVfb//oS/qGV9+h207s5v47+71IP/voc/riu87qtbefWNqxoCECCvQexVcsxEZxt1I4ofOVQTpovdLM1+ZvGzXOqTNp2nmz/whQZtLAFIkC04byA7eKBu6R+TpBWZ6lNOjsA9bAd7aXZb6GQbDc79BJma9Scv2gAIAN55x07iHpG/7h0n6LDz32gv7Wh9+vt37Fl+m2O07m/jvX9w70t979a/q7n/VGvfYL71vasQBNw1UIC7GmL0kKuuWZr8QOoPVaHjtQ2vmafKXzrcXKci0pvm60QedrUexI/JX1X2Bi7EDzrx+or2kyX8Ngyet70kBTiTWCtbtxGKkXLfp96JbeRTjIfC3u0eO+HZgPxVcsxCXF17LYgYDYAWCKbdWu0a2fxjp1Crb80fmK8sy+NJdidceDygyKMwWxA/z1lptq4BaFJazHNJ2vWmbmq7WSXMn9FcVX1MPr/+Yv60/+m/cs9os4q0HpczmuH05RfGXHCjAXiq9YyKD4up3/LwShwsCR5Qi0PNPS2uLYAdH5hmnWB7f5G8lnQnaKOl/lX77w95uLzlfUmO9s75ZkvobLzHV3ybC5SbEDXD9QA+958tJiv8AKsot98fVYSfF1qWsaaDCKr1iINfEJOijsfA0UOkvmKzAp81Vq9AN0VBI7ULJbEW1RWnylc2mTGR87UJj5HH/lNqHAxIFbFF+xPr7ztaizXRrsblnKs4BNiq8tvr9C/R1GpqJfafmxAzcOI+10w9Judt/5annAB2ZC8RULccYP3CrJfA1IfAXaXlwyziksqLKmN3G8QW+vqQemYNOkxZmCzriQh7hyNip/2Kb4ijXysSJFmc7SkvMhbfwcQvEVdba3H6U/XqhbdAWxA9cOI53YLZ/JzktTYD4UX7EQm970lGe+UlRB600VO9DchwNrXeFAjpDMR9iS7r4WrI8mmzSQZzBwa1VHtGHKrh2SpICTJ9ZmmsxX/+J1Kd+mPnaA6wdq7Op+P/3xxRu9+X+hFcQO3DiMSiMHpEFcENdtYDYUX7EQFyUXkJKbnlCOV2NAy4uvUcnALW7iUJ5r2fzO8CYzaSZk0cAtBneUmjhwi+Ir1qdvJme+Dl6wLKPzdcrMV64fWKO9g0Hx9fzl/QV+JaelD9w6iEqHbUnZURVce4BZUHzFQqbpfA1l6XwFyh6gG/5w4LcTF8cOxF8JKGmxlg+ka7JBJuSE9c/fbz4GbqHGIju583UwVG8JBzB15ivnF6xPtvP1/JUFiq9OS898vX44ufjq44JYVsBsKL5iMWbydp9AjpMzUPYA3fDMV+Om23bMeaLFWt4Z3mSTpqHzEDeBsxRfUVuTYkWkQbQQma9oq739ijpfnV167MA0xdel5jhvsP2eIb8epSi+YiFuUuerAjpfAWm64lJDOz/NpM7XtCummf/9mEKLO8ObLi2+FkxD5yFugrJhdBLFV6zVVJmvy4wWmZj52uyX29gMe1V1vq7gOeHGYaTjEwduERckSZ948ZqevXRTknSzF+lL/v479MPvfnrNR4U6K19ZwATOTDNwi5Mz0ObOPl98Lcp8ZeAW4vVR8PBOa/RGi9LizITO15Ud0YaZmPlK8RXrM6mzXVp25mvyHELmK2rMxw7cffqIXrl2OP8v5NxKYgcmDtxa5preAH/zZz+iq/t9PXb+qu655ai6YaDDyOrSjZ7e9cRF/ekvfmDdh4iaoviKxZjkTV5Z8dU5OtqAqTr7mrlOfOxApzB2gIFbrdfizvCmS7clFw7cir+29SFuorK1ISUDtygsYT2m6XxNh+ot49t06sxX1gjWZ+8g0u5WqHtuOaKXrx3M/wutKHbgxJTF17Zett/71GU9d/mmbhxGemnvUNcPo/Sf/fYTF/R1//Q39b9+/SP6qodvW+NRoo6IHcBiJmYtBQoD29qTM5AqzXxt9sOBMeXF17TzleJaezliB5pqEDtA5vNcrJmc+cq5E2vST67vW0U7F7Tka7ydPHsi/s25fmB9rt7s69SRLd12cnexztd44lZVhzXGWKeDvtXR7WkHbrXz2vPS3oGuHUSyTkOF104Y6NpBpI+/eE3f//MfTXf+AR7FVywkzXztbOX/C0nnKx0taD3bb20mGZ2vmKi0M7zZ66Pp/DT0wuIrmc/l3BTFV9YG1sTHipTFDoTLvMb7zNeirdgUX1EDewd9ndzd0m0ndvTytUPt94z+8a98Qs/Pmv+65NgB38m+s1X+ewyy2pd2KLV10De6dKM39vn3/f7P0vf9vtelP3/ilRt6+0df0n//xMsUYZGi+IrFTBq4FYQKZenJQLs5F6+VkpcU8b/XzIcDP/kzLNkqFQSi9a3NyjrDJUlsrd5U/QmxA2Q+TzDVwC3+8LAe/bVnvtL5ivq7up90vp7Y0c2e0bf98KP65+/4tP7lf//0bL/QkmMHelPEiEjZztelHUptvbQ3iI3wfxWvOndM3/qlD+qbPvceSdKf+ML7tN0J9Q9++eP6M//2d/V3/9vH1nGoqCGKr1jMFMXXQK6Vb8aAVLpO2ll89Z2vRZ1vUvwWnfNEi03MtaTAtKnMpM5XOt/LTRy4xYsJrE86UK8kdiBYZqFmUvyZ6rVz4neeuKDv+IkP0enfMnsHfZ08sqVbT+xIkt75qQuSpEefujzjr7Tc2IFeFK+T7ZKXKVK7s9pfuDoovt5/5qhee/txfcGDZyRJp45u6T1//av1/d/4Br3uzhP6zCs3JEn/5reenL3LGY1E8RWLSQduFWdZhmLgFlrOr5NOOzsz/MCdsKT4GgYBma9tNlXxtZnro+kGna9kPs+FtYEaiyasbynb3b6ENe6m7Xytx/nlvz32gn76/c/pRs+s+1CwQnv7kU7udnXbid30sz/85rv18Rev6eW9GQZwObfUztdpBuhJ2Rcq9VhXq+Q7X7/y4Vv1DW+8Uz/xP3+R/uYfeH36z28/uaswDPTGe05JUjq87HefurT6g0XtUHzFYqbY7hOIgVtoOetfUrSz89W/Ge9MiB2g863Fptpa3cz10XTRhIE8dL5OMM3ALdYG1mSabco+13kpa9w/hxRdP2pWfH364k1J0qXr45mRaK6bvUjHdrq67eRO+tmf/7JXSZK+52ce00F/2mL8kjNfo+R6PaH4KsUvVeqxqlbLd77+iz/xZn331z2i00e3dWR7/Pzz2fecliT9j2+9X9udUB99fm+Vh4maoviKxUyxnTqUo6MF7WYmDKar2ba4qpmpMuGCujwbYR0oMDVWZK2CoLzzncznEpMGbpGHjDVKX66UFGuW2t2eNoEUFV/rdX/1zKWk+HqT4mub3Dg0cfH1xKD4+ro7T+qvf8MjesfHX9Y7Pv7ydL+Qs1pq7IB/mdKdpvgatCJ2wFinq/v99OcvXj3Qid2uju+U7EiR9EWvOquTu119/Rvu0MN3nNDjFF8hiq9Y1FSZr1a2Hvc8wHqkna+bsS2uamaagVtq5/YlJMi1bKzIutI8SInM51IM3EKN+ZcrnQmxQtKyOl8nZL7WYGdRZKw+8Mxl9Y3V+ctx7uOlG4drOx6slrFO+32jo9sdnTqypYduO67v/0NvkCT9sbfcK2k4R7SU00piByZlvkrt2bH2b3/7SX3Z33+H9ntGh5HRb3/6gu695ejE/9+9Z47qw3/ra/U5957W6+86qcefv8pzDii+YkFTvHGm8xWtl2a+tjN2wA/cmvRwxlmixabJtcRGiowt7XqXyHwuNfHFBF3hWJ++mfxyxTfq2WVUaty0sQPrWyNv/+hL+qZ/+Tt675OXFCV/BheJHWiNm734BcGx7a6CINDb/9pX6Fveer8k6dSRLW13wxlyX5ccOzBl5qvUnh1rv/qxl7R3EOmx81f1r37jM/rUy9f1XV/78Ey/xuvvOqnLN/vTF9nRWDzNYDHTdL4614o3Y0Chlme+TtX5GizpwQybgaFCjdU3rvTFi9SeDpq5EMmBGpv25crSTPEcImmta+TC9bjLNTtw5zKxA61xMxmudnRn/DweBIFuP7mTDnGaaMmxAzMVX9X8HWv7PaP3P31FkvTBZy/r7R99SV/w4Bl91SO3zfTr3HX6iCTp5Wt0vLcdxVcsJJhiO3Ug285EbsCblPmaZpI1c6H44utW6TRkOl9bjdiBxjLWTTU5uaGnv8XZaELxNWjstQP1F1mn7oSXK/4fLyUf0uea1Th24NphfA/44eeupp9dvEHxtS1uJH//RRmht53Ynb4o59wya6/qzTRwq/n37e97+rJ6Jo5W+a1PX9Tjz1/VWx88M/Ovc/rotiTpCi9dWo/iKxbjt/uUbKcO5VoRyA0USl9SlA1NkZr6lqJvJscOxJmPzfzvxxQmFZgYKrSxImsnFmfa0EEzNzdF7EBDrx2ov56x2p4wnCdIi69LOACTFDM62wW/eQ2Krwdx8e0TL15TGEi3ntjRZYqvrZF2vm7nn8dn6nxdUezAdndyhTdswY61jzwfvzD5ytfeqt/85CuyTnrLA/MUX+M6yZWb/Qn/JpqO4isWEkwRdB/I8liAdjPTxg40c6VEU2xjonmr5SZ29zFUaFP1zeTO1zZ00Mxt0sAtXkxgjSJj1Z2Q+epjB5bygmUDiq/Xk+Lr+Sv7OnNsW+eO7+gSxdfWuH7oM1/zz+O3ndjVy3vTdr7WKHYgCBofF/TS3oGO73T1rV/6qvSzN99/y8y/zi1J5ytxIyh5lQ5MFqQDt8piB+h8RcvZSR3iPnagmQ/QPnagrPst3nbMeaK1yHxtLGOnzHxt+lPcvKaK5ODPDusRGTcx8zVI7nGW0/k67UDT9a0RX3yTpLPHdnTm2BaxAy3iB24dLYodOLmja4eRbvaiwu7YlHODZ4YlmK34qsYPynx571C3ndzRlz50Tj/y579Qz166WRgfUebUETpfEaP4ioUEbnLQfSgnx0MV2myKbORYM9dJ3xdfSx7Q4ps4tJazFF8bqj/lQB7Wf4FJA7ckcfbEuvSM1fakTOfka1s7X33sgCSdPb6tM8d2dP7ylbUdD1brxmHcgFHU+Xr7iV1JcaHvgXOTSjNOy+x87ZkZM18bful5+dpB+vfzxa8+J716vl+nEwY6udsl8xUUX7GYcIriqyQemtFukzoz1PTO1/i/q2xrYhtu4lBiqqFCzVwfTRcZp60J25LJfC5BJEcrPX9lXx97YU9f/brb130opW72TO4U96w0dmAZBzCx+Lr++6vrh4Nut7PHd3T22LZevnaoyFj93Ief18XrPV07iHRit6s/92WvKvmVsIl85+uxgo7J20/Gxb2X9g70wLlj5b+YW3Lma5Rkvk7Z+drU67axTp948Zpe2jvU5953upJf85Zj27pM52vrkfmKxUwROxBr5skZmIqdlPnqHw6auU4YuIWJpokd4DqykaIpYwdY/gUmDtzixUQT/bWf+KC+9d8/qucu31z3oZS6fjh5q7Rf/ku5xk8dO7DO4ms2dmBbX/zqs7rZM/q1j7+sf/Ubn9H/9euf1n9899P6kfc+s7ZjxPIMOl/z18m5E/GLg6miKJxdTezAVAO3mts08SPveVrf8M/eqWcu3UyL44s6fXRbV/YpvrYdxVcsJHSRrDrFF4K0qGRWd1BA3ZjkxnvSw0FDi0vRFNuYArYdtxuZr40VWautSbEDIZnPhaYZuMXZs3GSDSP6yUefW++BTHCzF03MQPSPAnYZp/ANiB24nokdOHd8W2975DbdcXJX/+adT+qTL13T5Zt9XbzR05MXbqRdkmiOG0nx/UhB7MCZY0nx9fo0Q7eWGzswU+armts08dyV/fTHt53YqeTXPH1ki9gBUHzFYgJnZMseCmoQdA+s3aTM14bHDkQ+dmBS5ivniXaydsrMV74/NlE8kGea2IHVHM9GcW6KtUHbcBPtbMVr5mc+UO/i641DU7id2gvS2IF1ZL6u//5qqPP1+I66nVDf/Pn36r1PXRo67zknffzFa2s4QizTjZ7RdifUdjf/Onjm6Cydr8uNHZgl87XJTRPZLuXbKup8veXoli5TfG09iq9YSDix+Lr+mx5g7SZui2t27IDvfO2WbD0OqR+0l98ZMelawnVkI0XWTowdiAducQIYk0Y7TXrJzZ9d01y4Hj+kP3tpXx945rIef/7qmo8o343DqHCQkJdmvi7j23QDYgeGBm4lXY5//AvuTeMYspsHH39+b5WHhhW42YtKc5G7nVCnj27p4vVpi6/L73ydJvM1bHDTxNVMPMDtVXW+Ht3WFTJfW4/iK+bmnFPHRVN1vjb15AxMxfrBdJMeDpq5TgadryWxAwoau30JE0xTYBLF100VGTcxdiAe3LGiA9okjrXRVhevH+q+M0clSd/yr9+jv/QjH1jzEeW7cRhN7nxNvi4n87UX31sVxp+tN9apF1kdRjZ9+Xz2eFzIufPUEX3dG+7QQ7cd14PnjuneM0d06siWHj9fzyI75nfj0BTmvXpnj23r0jSdr8uOHYh87MDk3yMIlhQlUgPZIunZ4wVd9TM6fXRL1w4iRaahf2iYCsVXzK1vnDqyclMUXwMeDNBmaWfGhNiBhnYvRZbO17VxTnrH90vn37/uIymWvpwgdqCJ+tapG06IHWjw4I6FTLU2OHk2jbVOF2/09GUPnZMUb1t+6uINHfTrNT/BWqebfTO58zVZ/kt5wWJ6xZED0to7X33e512nj0gadL5K0j/6o5+jn/ifv0h/+W2v0f/ytof0+Q+c0Ts/dYGGlYaJX1CUr5Gzx3Z0YZrM1yXHDvSNVRCUD8j1mrZj5eL1Q/2+f/ZOPf78VV3d7+n+s0f1f/7xN+k1t52o5Ne/JYmXuET0QKtRfN0U11+Rfvl7pU/84rqPJBVZq66MbFE3n5S5QFB8xZLcuCA9/0EpqvHFLM18bWnn6xSxA0EQ0Pm2DHvPS7/5D6Uf+qp1H0mxqYuvXEc2kbG2dO1Lyciohp7/FuLXxsSX3PzZNcnV/b6MdXr1rcd1d1K0c076zCs31nxkw/b7Rs5p+szXZXW+FkUOSGsvvvq81z/85rv1F77y1Wk3syQd3e7qlmPb+qbPvUd/9C336mtef7vOX9nXR84TPdAkN3qRjk7qfD0+Zeers0uNHegZp61OmK7ZMmHD7tvf8+QlPf78nr7npx/T5Zt93X36iL7xTXdX9us/dPtxSdJjz9Hd3mYUXzfFT/4Z6V3/Qnr3v1z3kaQiO33na1OLSqiBH/4m6Qe/QvqVv7HuIyk2MZMs+drQ4lLa+VoWOxAsaRhH2z2f6Xg9/37p4hP12yeWFl8nXEsauj6aLh64NUXmK8t/XBrJUfbg3uzM8Da6eCPugDt7fFufddfJ9PNPvVyvYUy+q3NS8dVnvq6383U968PnvT5yxwl999c9orDkRdTved3tCgPpFz/ywqoODytws2cmd74e355u4NaS75P7xk6V9+o1KS7spb0DSdLjz1/VpRu9tFO1Km++7xZtd0O9+zMXK/11sVkovm6C/oH07HviH5v6BDVHxqkbmCljB+q1VQoNcuXp+OtT71zvcZSZlPna9NiBJN+ovPOV2sFSPJ/JCfyl75H++Zul9//79R1PnknTqiUGbm2wvrGlL14kn/nKCWDMVAO3KL42jR+2de74jr77ax/Wv/nTb1EYSE+8fH3NRzbsRi/+/pxUWErvcJbS+dqffO2QVnr9+LkPPa/rh5GeuXhTP/Hos5Kk4zsl3bmJM8e29RWvvVU/8ehzOox4bmqKF68e6Myx8qFNZ47t6PLNnkzyhuJXHn9Rf/4/PCo7+sZiBQO3psl7lZI4kQZddp6+eFNS/JLoyQs3dOro5DU7i92tjj733tN692cuVfrrYrNQfK27Fx+TfveHkm3LgbR/ed1HlIpMHDvgJm0VlXgowHJYKx0mnSAvfzTOtnzpo+s9pjyTMl8bvk4Gna9lma8B246X4fkPSHe8UXrgywYv8S4/ud5jGuWLr92ShxO2Vm8sY93E2IE4Ow5jph24Ff/Lyz4arIifen72+LYeuv2Evvp1t+v+s8f06VdqVnz1na8TtlT7ztelfIfWLHbg2Us39Zd/9AP6R7/8CX3lP/p1/bvfeUqSdHy3/M/I+zNf8qAuXD/UL3yY7tcmuHKzp/NX9vVZd54s/ffOHd+Wc9Llmz1duH6ob/vh9+ntH31JV/ZHm66Wn/m6NWXna9MG5T598YbOZYZrnT5SbfFVkt76qrN6/PmrunZQn2Y6rBbF17r7V5nt1K/56loVX/vWqSMzIYssvuEKGnRyRo0c7sU31A99Tfzz3/yH0s//1bUeUq6Jma+r78xYJZ/5ulUydCcQ086X4vkPSne+SXrwKwaflW5hXoP05cSEraMNXR9N1zeTB25JdL7mmjrzVY19eddGaexAplvuNbcd1yderGfswPGJsQPx17EuviqY3hQv7rSy68eLydblX//Ey7JO+v/84Tfqe7/hdXrj3aem+v9/+UPn9Opbj+nf/vZTvJBugI8+H+f3vv6u8uLrmWQQ2688/pK+/v8c7OS7dGNkCJezGrxwq14vclMXX8OgWa/8nr50U2+5/4y2u/F//+mKO18l6U33npZ1g+8LtA/F1zqzdtD1IEm3vz4uvtbkYmyMU1dWboqBW47YASyDfxnxmt8z+OzKM7VZIymTPEAXZr76U3HNjrsikY2np5ZlndH5tgSH16T9S9LZ10ivyhRfb1xY3zHliZKHi0ndS3Vb15hKZCdvY2za9sXKTJWHnHzl5URjPHvpprY7oW7JPPy/7o4TevLCDR3063M/faMXf38enVB89d+jy8l87deq8/WVa/H1zG9h/vo33KE//+Wvmmp6vBQPJ/szX/KgHjt/VY983y/ptz9ds+s1ZvL4lMXXz777tHa3Qv31//yYdrqhvufrH5E06IJPrSB2wBcfJ2nSwC1jnZ67tK/7zx3VXad2JUmnj1Sb+SoNvg8ep/jaWhRf68xvDd05JX3Zd0pHzsRvePs313tcib616sjITRqSIjpfsSS++HrqXukb/y/p8/6sdO2F+m2rTjtfix5Qmt352jeutOtVkkTmY/Wuno+/nrpHuvvzpK/6G9Lu6foVX6fJfBWZr5tqmoFbTdu+WJm0K7wsL5DYgaZ5/zNX9MZ7Tg1lJT9y50lZJ326RrmvNw7jQvDxCZmvg9iBJXW+TjVwa7XFVynuCD41x9blP/Lmu3XHyV0dRpbi64b68HNX9Osff1kfef6q7jy1q7PHyzNf7zt7VP/sj3+uHrnjhH7oT71FX/7QrZKkS2NDuFYROzBlcbdB9+3PX9lXz1jdf+aY7kiKryemjAqZxW0nd3Xu+A7F1xaj+FpnL344/vqnf1b66u+TjpyOf16T6IHIOHVlyrewrvimBy1zcCX+euQW6XO/RXrrX4h//slfXtsh5TL9eJ0Uva1u+MAUY+3Ero8waNj+pTrYey7+evLuuHPuK75LuvOzpZs1e5ibKnaAiWybKrKTYweatn2xMr4rvDvNQCH+BJvgMDJ67Lmr+rz7bxn6/OE7TkiSPl6j6AEfO3B02szXpXS+1rf4evfpIwrm6FI8ut3Vb3/P23Tu+LYu3yQbchP9g1/6hL7nZz6sT750XY8ka3eSr3n9Hfqlv/rlet2dJ3U2yR69OFp8XXLswCyZr026b3/f03Ft5bPvOaWHbov/vvpLaut9w90n9fjzV5fya6P+KL7W2Qsfjgs2t31W/PMjyY3Y/pW1HVJW31htKZpu4JYovmIJ/IsIvzbOPSTd/yXSf/970vVX1ndco2y/OO9VanzsQH+qzrfmvEGvjbTz9e7BZ0fP1bDz1ccOkPnaRJGxEwduBQ3avlipadeGpKZeP9rmI+f31DNWb75vuPj6wNlj2umG+vgL9emYuu4Hbk2IHfD1x6Vc42saOyBJd99yZO5fpxMGuuXotq7cHO18RN055/T481f10t6hPvPKdT1w7tjMv8YtR5Pi64pjB3pmtszXTb9vv9mL5JzTe568qJO7Xb3uzpP67q97WH/5ba/R173+jqX8np9zz2l98qVr+slHn13Kr496o/haZ0/8mnTHZw+C5NPia006X63TdhCVb4dLYwd4aMYSjBZfg0D6+r8fd8R+7GfXdlhjTFT+cNDw2AFjJ9/M0di4BHvnJQXSiTsHnx07V8PO1yliByi+bqy+dUPbp/PE658TwJhoykgOifXREI89d0WS9Ln3nR76vBMGeviOE7XqfL3Zi2MHjm1Pih2Iv66383U155dXrg+Kr/csUHyV4gLc+LZz1N2Lewdpx/JhZPXA2dmLr9vdUCd3u+MDt5YdOxBZbU9ZfN30uKDIWL3pf3+7/tKPfEDv/swlfcGDZ9QJA53Y3dJ3fM3DU2ffzupbv+xBff4DZ/S9//kjtcrwxmpQfK2rFz8ivfAh6bO/efBZzYqvxlptqy83xU0Po3SwFGnx9fTgs3OvHf5ndWD7EwamNHvbaDRl7MAm38TV0tXz0ok7hgv/R89JB1cHRZ068LEDk7ZWU1zaSMa6yZ2vauzpbzH+xUTpNPdmXz/a5sW9Q213Qt12Yvzv/JE7TujjL9an8/XGYaSdbjjFy5X4e3Q5na/1iB2w1unbf/h9esfHX9ZOUrS5+/RixdfTR7d0hdiBjTM6yf7+s0fn+nXOHt8Zjh1I18+SYwe60w6H2+zLzrOX99WLrH7hsRf05IUb+pLXnFvJ73tyd0t/9kseUM/YWr1Mw2pQfK2rj/xUvE35jX908FnNiq9947QzZfFVjjc7WIL9K9LWseEH0+6O1D0SF5jqwhA7sDXFpN9m/tev0d5zcd5r1rHk5vLmxdUfTxE6XxvLORcXXyfEjoRBsJxhPJMcXJX+0cPSD331IKZjTX7n0xf0sZEt5fsH+5Kkp65GJf9PBm41ycvXDnTriZ3crNCH7zipC9d7Q1vbV+bmJek3/6FkB+fhG71oYuSAlPkOXUrn64TYAW/J149Xrh/qlx5/UZL0BQ+e0XYn1BvuPrXQr3nm2LYuEzuwUd7+0Zf0rf/+0aHP5ul8leK//0t5xdclxg7Mkvm66XFBn3klHl740G3H9T1f/4i+5a33r+z3fuM9pyUNdjqgPSi+1lR08UlFp+6Xjp0dfFiz4mtknLYVSd3d4n9pxdt90DL7lwfrIuvI6XoVX62ZMnagmevETLHtOAyCpv7nr8/V88N5r1Km+Fqj6IFptlYHoSguDfvmf/Uu/ecPPLfuwyjVN/Hf2TSxI3YdtfULn5auvyidf1R68jfWcAADf/0/P6YfePsnhz77xPl4nb7rqZLuGO6zGuWVa4c6l9P1KkmvS4duraH79b/+Zekd3y89++70o5s9oyNb5ZEDUmbg1jLO4TWJHXjm0s30x0e3O3r///Z7F+6kO310W1du9olk2SA/+t5nJElf9fCtOntsW50wmDv7d6z4quV3vs6a+brJ92VPJMXXn/z2L9K3f8Wrp/7vrsJdp3Z15ti2Hjtfo2dVrATF15r6wMef0Acujvz1bB2NbzBqUnztW6udoM8UXqxPUfF191RtBtNJSmIHphhM19B10p9q4A6Zj5W7eUE6duvwZ0eTh8EbNRpIl3a+TugOp/M1de2gr/c8eUnvfuLSug+llEnaYqaJHVlp56u10g9/k/TeHxx8tuZrxqUbPb149SD9+adeuqZPPBcXXz99qWTrcXqfxfpogleuHeZGDkjSw0nx9ROr3Kr6sZ+TfuD10jPvin+eyZs87Fvtbk1+lPTF16W8YDH9WsQOPHNxUHz9qodv0/EpOoInueXolnrGptm6qDfnnD747BX9sbfco3/7Z79A9589qntuOTJ3Ue/sse382IFlZr6a6TNfww3pfL1yc/ja6n3mlRs6e2xbp4+WZaovRxAEeuPdp/Th5yi+ts3iVwZU7kPPXtExs6fz7txw+38QxIWm/Xo8bPnO12CKgVuheCjAEuxfHs579XZP1avzdeI03uRrQx+eIzPttmNUqn8gbY10XBy/Lf56o0adr2nxdcK1hOJ8yj9IvLg3/kBRJ/2k2jLp5Yuk1T7E7V+WnnjH8GcHV1Z4AMMiY7V3EOnFvQPt94wOI6Pf+09+U384fEHfvC196mK8RpxzeuX6oW47kd1xROxAk7xy7VBvvj/npbLiDMjbTuzoYy+sqPi694L0498y/Fk0iDw46BsdmTBsSxq8H1he5usUsU5LvL/6qfc9p1987AUFgfTY3/raiQPIpuUn3l+60Zsq3gHr9cylm7p0o6fPvS9ev3/pba/RtYOyyJhyZ49v6/KNnqx1CsNM7v3yGl+TusP0ma+bMKvh9/zAb+rC9UN95u9+g6wb7MT7zCs39Kpb54uEqMKD547p/U/Xo6EOq0Pnaw39+KPP6pbgmi65E+O5TkfPSTfqkdXnB26VD4JYzRtntNSmFF/thMzXhj88R9apE06x7XgDbuI2hnNSdBDnH2f54uv1l1Z/TEWmyXwVA7eyfNE1r5ujTqIpYwdWHjuSjd3YPiHtrHe3xF7ygH7h+qF+zw/8hv7ij7w/PrQg/vyJS30dRkbf9VMf1hf8H7+mpy/eGPyf2WHUGH1jdelmT7ceL76vvv/sUZ2/crPwn1fqwifGP+tdT394EBntdqcvvi7lO3TNA7esdfrOn/yQfu3jL+uuU0d0fKebm9c7j1uOxf9dDN3aDB945ook6XPvOy1Jetsjt+sb33R38f9hgjPHdhRZp70D//e/goFb0WyZr5tw2blwPa6lfPt/fF+ax+uc0xOvXNerzh1f23Gd3O3qei9i11/LUHytoceevaJbdE2XdVwvjD5YHb9VuvHyeg5sRN93vk5RfA14aMYylMUO1Kn4aiKp097YgchOfpO+KTdxG8P0JLnxl2M7J+Oc7msvruWwck0VO7DhY3Ur9sKmdL6a+No/TebrSh9AsrEbp++NX+KtIdLp/c9c1m996oKu3PSdrdL5K/v67U/HL9n/4Ovj3P9929WP/+6z+qn3xRm/PqtO0lK3oGK1Ll7vyTnptpPF99W3ndzVy3srGriVtyYOB997+z2j3VkyX5fS+bre2IFXrg/+Lk7sVtudesvR+JrI0K3N8KHnrujIVkcP3Xaikl/vbFJ8T6MHVhA70DNOW93pM183qWni1z/xsn7jk6/ofU9f0jOXburijZ7eeM9iQ/EWcXy3K+ekG8SKtAp3bDXTi6yeeemCdoO+LrsTemn0werYrbXJ6ouSztdpiq88NKNyzpUUX0/Xq/g6qfO14Zl9xrrJma/arJu42uvHU9LHYgeCQDp+u3S9Hi/xJA2Kr5OuJQ1dH/N4KSm+Xt3va79nats5cdCPHyqObE/R+bqKA/Ky3/+nkuLrlWfioUIrvHb8H7/wMX3Pz3xYV/bHO9tO7Hb1RffHXTk9dfXvf+ep9J+dv7yf+Tebff1oE7/brazz9fYTu+PPBsvii6/bmWJStvN1yszXQexAlQeXWFPswI//7jP6hQ+/oGczg7aqfhnmsyj/1P//vcPd7qilj72wp0fuPDEx43xaZ44NYickZWIHljhwKzJTZ74Gqvfj/e8+dUk/9JufSX/uB4D+y19/Qu95Mo5w/IIHz6zl2CTp+E583rq+QDQFNg/F15r55EvXdMzEU0wv6/j4lsJjt0nXa1J87ffVDex0xVcyX1G1/n58013W+VqXu4JJma8Njx2IB25NKr6s6GDaIkquHd3d8X92/PaaxQ4khafSFxQUX7NeyDzk/8JjL+ih7/1FvfNT9bg3yNpPiq+TtiavPHYkm3l86p74hd2z75be/x+kZ95d+H+rkrVOH3thT89d3h8q4Hivu+OkguTFxO7uUT3xyg3dc8sRbXdCPXclU3wldqAxXr4Wr+vbTuactxO3n9zRjZ7R9cMVPLD74usdbxh8Nho7MFPna6VHF/+Ca4gd+NRL1/S//vRj+os/8n49ezleu2++77T+yTe/qbLfQ5JuzQxe+81P1SinHWOcc/rYC9f0ujtPVvZr+uLrxeu+83kFsQPGTZ35uvJBmTP6o/+/d+n/+G8fG/rs8+6/Rb/28Zf1H971lG45uqXX3Lq+2IHjSaf89UNiRdqE4mvNPHb+qm4J4iD9a+GpnM7Xc1L/htRb/xtQ24/f0IdbJcXX5AJB7AAq5x8Kioqvzgw9JKyVjSYXlqTGPjxPM3ArCAI6X6tU1Pkqxbmvdep8jQ6lsCuVFegDMl+zXsq8mP3On/yQIutqOTV3P9lOtzthAM3KY0eyO4jOPDicHb6itfHUxRvpFPN3PTHI8j+a/Fk9fMeJtCv8c+6/Nf5672ndeXpXz1/J67Dj/LnpfJHFbzfOc3tSmF1J9+v+5Tg3/MyrB59lYgcOpo4diL9Wfo33L+6m6nyt7vf+5+/4dPpjf979kT//Vn3Vw7dV9ntI0qkjW/qlv/plkqRrBxRo6uyFqwe6ut/X6+6oJnJAigduSdnO1+XGDvSN1X7f6Oj2dPEZQSDZmt6Wffrl/KGEf/sPvl7Htjv6yPk9ff4DZ+JBZmtyIhmit8hQNmweiq8189TFG7q1E9/YhEfPjGe+HotvwGsRPZBMPA22it/Qk0WGpZlUfJXqEz1g+hMyX5u9bTQeuFV+gxMS6Vmtjep87Umdspd4Sq4lfIN4L1w90IPnhqf09qL6nT8O+vExTep8XXl23I1X4gGmf/K/SG/+03Hnq7eitfHRF/bSH/9Opvj6xrtP6Qf+2Ofoz33Zg/F9Vmdbn/+qs+k/u+vUEZ2/nOmUZbBpY9zsxQ/hx0sm2/s82JUVX4/cIp3KDA3KNH8cRNPFDvhGjOqLr1MMa1zC/dXTl25qO8nF/LkPPa9bT+xMVYSex8O3n9BWJ6BAU3MfS87ny+h8vXQjyRVecuzA5aTIe+7EhPsx+cOob+frz7z//NhnR7c7+qw7T+pHv+2t+q6vfVjf+bUPr+HIBgadr6ztNqEyVjN7+5Hu3o47lrZO3Kr/+qHn9b6nM4H3flL1jfVvP7FJ8bUzVeYrYdKo2CYVXydmvvpTcT1vYhYVD9yaMHBHdL5Wqqzz9cQd0v4lKarJEI+JsRwidmDEi3sHetO9pyXFD2gndru6mpMbum6DzNcJna9a8cuXG6/EL7Nf/VXS7snhztcVvdx+/Pk9dcNAZ45t65kkduBLXnNWX/HwrfrDb75H9589lm6p/sqHb9VWJ9AXv/qs7r7liM4TO9BI+8nLirL1ctuJ+IWaz4dd7gFdie+xTmaLr4OOsoO+mfhiRVpirNBUxdfqX07s7ff15Q+dUzcMdOF6T3edzrnOViQIAp3Y3aLzteZ+69MX1AmDeMdCRXa6HZ3Y6Q4Gbi05duBC0nl/rqTzPit+abqUQ1nYr37spfQFiSR1wkCfc89phWGgz77ntP7iV71Gr729ur+refiXbGS+tgvF15rZ2+/rjq34rfK5226XJH3HT3xw8C8cOxd/rcGWUZcUX8PtsuKrjx2o6dkZm6us+OofpOtSfDXRdJmvDS0uRWaKgVt0vlartPPVv8Rb/3VEkmQOyx+eJYqvGQd9o0s3enrVuWP69//TF+jX/tpX6OTulvZqXHyd1B238uy4G69Ix28d/HwNna9PvHxdD547ps9Jpi2f2O3qP/25t+ovfOVrBv9S0vn6yB0n9ZG//bX67HtO6+7TR/TytcNMp3OzM8PbxGck75RMG799HZ2vD3ypdO9bpaNn09gB55z2+2biixVpkPm63tiB6q4fV/f7uu3krr729XdIkh66bbm5kSd3u9rbp0BTVxevH+rH3vusvvFz7tKJ3Qkvkmd05vj2IPM1jR1YTvH1YtJhe7Zk4F9WoKCWwz6fuXhTn3zpuv7EF9yXfvaDf/Lz9IN/6vPWeFTjfPH1Gp2vrULxtWb2Dvq6tXNDUqDv+INv1Te+6S49femmDqOkc/SYf2hef+xAWnydInaAzFdUzhdfsw/NXi07X6eJHajfTUwVIjtN5mtj//PXozTzNX6xp2s1iR4w/cnFV5H56r28F197bz+1q6947a265di2Th3Z0l4NO6N8MenIhC25K8+O852v3lDm63Lvr5xzstbppb0D3XFqV1/ymvilus9/HWJ6UrK7aCfpMLznliNyTumgn6ZnhrfJYd9odytUUFJcOb7T1dHtjl7aW0Xn6+V4bZx9tfStvxwPp0tiB3rGyjlNtd3e/+dUvsbTztdpduBV85s757S339epI1v65//D5+pn/sIX63u+/pFKfu0idL7W23977AXt942+/StfPflfntGZY9uDzFf/gm1JkX5p5vTxKTtfw/pddm72Iv29X4qHbP2JLxwUX+86faTywviiTuzS+dpGFF9r5up+X7d09qWdEzqyu6Ovft3tck568kKSsZRmvtagYym56SkduNXw7dRYo7LO150kc2n/ysoOp9SkbdUNz0aOjFW3bJiS6j81deOkna855+cTd8Zfr72wuuMpY3pSd5rO19UcTt29mHS83Xlq8OLz1JGtmsYOJJmvE4uvq+58vRBnvnrZ68iSO1//9Tuf1O/5gd/Qi3sHuuNkXECXJJO3fzNnkvtn3RVf3z5yPnm52PDM8DbZ75spXlQEuu3Ejl5OYgf6Zol/777z1ds+kQ4y9Wu7rEvXW17n6+pjB272jCLrdOrIlsIw0Jvvu0XnpuwUnNeJ3S6ZrzX29MWb2t0Kl9IBffbY9iB2wC07diA+p5w7Nt33c1izQbnWOv2VH/ugfukjL+o7v+a1eu3tJ3TL0fjZ6/TRehVepUzsAJ2vrdLsJ/4NtLff1/Gwn3Yr+RP5p15Kpotu7cZdfddeXNchDvR95usUna/ioQAV278c56huHxv/ZztJjk/v+vg/W4dJma9Njx2YsvO1rtlRG8l3vnZzOl9P3RN/vfrc6o6nTDRN7ACdr94LV+O/22zx9eSRema+7qexA5MzX1e2/p2TDvcGOySkwQ6KraNLf7n9+PNX9ZkLN/TS3qHuOLWr15Q9sEeHYy9QXnv7Ce10Qz32nN/ZQexAU+z3JhdfpXhb8KUbh4qM1ef9nbfru37yQ0s6oMvDXeHbx6TDOPP1cMq1nVX5d+gaYgf8efbUkdUVc07sdmu5swGx5y7v655bjpZ2rM/r7LEdPXvppn794y8vPXbg0o2eumGgk0dKduqNqMt9+xOvXNeX/YNf19s/+pK+7/d/lv7S2x6SJN1+Mr5PuuXodN28q9TthDqy1aH42jIUX2vm6n5fx8J+mtP34LljCgPpUy9nikhnXi1d+NSajjDD+M6qyW+ciR1A5XxHRt5NyHbyMHt4bfyfrYOJpE6LYwemyHwNg3pmR22sJBZGebEwR8/G15irz672mIowcGsmPuvRP1RIcSGgjpmAs2S+rqx26LvCs5EcZ18db11+9dviuJr+8vI0/VATKf47DIJAP/XtX6Rf+F++dPxfNr2xLdVbnVCfdddJfXis85Xz5yY6f2Vfv/cHfkPPXrqp/b7R7hQZqmeOxTmQ56/sa+8g0k++7zn9zqcrHsTb34/XSrbzded4GjswbaSIJIX++l/1t+hUna/VvtxeR/H15O4Wna819tyVm/rsE9ek9/27yn/tb3zTXTq+09V3//SHtYrYgbPHt6cuIsc71urhfU9d1vkr+/p7f/iN+jNf/ED6+W0nd7W7Fc70kmiVjtPV3joUX2vEOae9g0hHgl76ULC71dH9Z4/p0y9nikjnXluP4qt/uJ+q87Uup2c0xuh2uKytI/H33qZ0vjZ822hkrbqdyZeburxBb4SopPM1COLu17p0vuYUmMZQfE29cPVAx3e6Q/ll9Y0dMAoDaXvC+o8731d0AuglWanZXROn75P+xkvSQ18T/3yJufrZKfW+gP6WB87o9XedGv+Xo8PcF9yfffcpPX7+ahxVQLzTRvvgM1f0qZev60PPXdHBFLEDknTueLwV+amLN9PPfvVjFXds50U7bR8fix2YKvM1+bq8gVtTxA5UtD7W0/lK8bXOzl/e13de+tvSz/2VONKmQl/8mnP65s+/VxeuH6ofLfd74OKNQ52dMnJA8rMa6nHdeSWJTPjGN909VDx+9a3HdO8tR9d1WBOd2OnS+doyFF9r5EbPyFinXfWHCpoPnjumpy4MbrB062ula8+vv6tvhqB7Ol9RudHtcFlBEGeTHdak+Dqxs6/Z20YjO7nzNajRG/RG8J17RQMRa1d8JXZgWi/tHaQTz72Tu1va7xv1onr9Ge33jHa3OhM7aVbaQdNP7qdGh9EFwUpy9f1DoiTdcbLk5bVU+GLikTtP6kbP6Pkr+2p6bE3T+RiRF68exJ2vUxQz/RCepy/GXah3ndrVR1+oeMCoLyIdOTP4bGdwXzVtV7s0yHytPnbAP4dMEzuwycXXuECTmwuNtbp+GOnyzb6Ou2Q2y82Llf8et5/clXPSRX/tWFLswIWk83Va8Y61pRzKzC5cP9Sx7Y6OjOwc+K6vfVg/9m1vXdNRTXZ8t6uf+9Dz+se/8ol1H8pSvHB1Xz/63mdqU6SvA4qvNeIv6LuZzldJuuv0rs5f2R/8i+deG3+98MlVHt6Y0N/0TBM7QFkFVetdHwzWyrNzvD6dr5OKSw2fVh3HDkzadqzG/vevRVnnq1TD4usUsQNcRyTFna93nhr+ez2VDJOoWy7gQTRdJ99KO1/T4mtON8zRpNDku/6q/q2NzUyulm4/NaHLqKDz9a7T8d//i3sHxA5suOevxC/KXrh6oIO+nS7z9diOjHX60LNXtbsV6isfuU0ffX6v2gfcK8/EX0/fO/hs+5jUvyFZO3WeszT4Ft30gVu//omX9U9/Nd55uNLYgeT3Yip6/Zy/HN9rOR93toSBjXck14lXriUv1ZcVO3DjcKbhceEqr9sTXLje07kT48d+dLurs0seiLeITtKY8s/f8ek1H0n1jHX6az/+If2dn/9oOigWFF9rZS8pvm67w6HO17tPH9XV/f6gLf3cw/HXNUcPBLN0vsry1gPV6t3IH7blbR9ff3e4lzM0ZUgLYge2Jg3cErEDleofxOffoqLmqXul6y8O4mPWyfTK14dE7EDGy3uHui2n81VS7aIH9nt2yuLMCjtoyoqvvstv/0rlv+0HnrmsP/tvfzf9eTcMJk+VNoe591h+2NoLVw+0rMnXWI3nr2Q6X3vTdb767rQPPHNZ9505qtffdVJ7B5Geu7w/4f85gytPx19PPzD4zBeY+jcyna/TF18rX+NTxQ4sdn/17KWb+k/veVrOOf3LX/+0PvbCnqTBOXcVTuzGMwNe2Kvw7xeVeO5yfD3pHEmaQa5Xv2vithPx+f6CL74u6Zx/8XpPZ4/NMpgqqM19+4VrsxWO6+IDz1xZ9yEsxWFk9FPve1bv+sxF/a0/8PqxhoE2o/haI/6hacv1hh4K7r4l/ob1N2g686AUdtfe+aqpOl/jC0QoR1MGqnV4ffAgkKcuna/WSM5MyLRseOyAcenb3SLxtuNm/vevRXQQd70WbU87dU/8de/51R1TEdOfInaA4qt3db+v00eG/7x8F9bPf+gFRaY+f04HfTPVtuS48X1Vna/JvdRo7IA0yLe8eany3/ZnP/i8fisZivSGu0/qDXefGgwiKhL1cu+x0uLrlf3G75xoqsPI6Lt/6kN671Px99qLewdx5usUA7d8LuNnLtzQfWeOpXnBjz+/V90BXn46vsc6mokd2E1yifcvZzJfp1nfSezA0jpflzew8e/90sf1vf/5I/qvH3peH3p2EO3gC6KrcDL5vb7un75Tv/tU9ecmzM/vTN066ouvy+h8HSm+LiF24GYv0s2emalLNKxR5uuF64c6N0NkQl386S+6X1Ky+6culewZHPSN/uC/+C39lw+c16UbPf0//+P79LMfPK+H/8Yv6R//yif10G3H9Uffcs+6D7NWKL7WiO983TIHQzl9dyfby/zWBnW2pDOvkl5Zbz5IaJKOqSk6X0O52mxNQEP0bsQF1iLbx+uR+ZoOpmtn7IBzLs58nWbgTn1qRpuvv1+c9yrFna/SYGvpOkWHkx+eRearJEXG6vphNLbl1W9L/Se/+kn92seXl1c6q2mLSWGwwldPeQO3PJ8jvoTYgU+8ONiJ8Xe+8Q36L3/xSyb/nwo6X0/sbun4TjfufG34zommevz5Pf3Eo8+lMRQ+8/XIFMXMM5nutAfPHdV9Z44mv0bFna+n7x8u9Jy8K/6694IOo+k7X/07huVlvlb38i4yVr/60ZfSolI/ydH+Kz/2QfUyL7YmvjipULbL9jOv1OC+FqnnLu9rpxtqezv5HlxC8fXM0W11w2Cpna8Xr8draVMyX3uR1WFk9M9/7VO6erOfFF83r/P1b3/jG/S93/A6OSdd28DBW5986Zo+/NxV/dUf/6D+2a99Sr/4kRf1vf/5I5Kkl68d6pvefPfEzP+2ofhaI77ztWMPh3L60uLraO7rumMHrO98nab4aulpQ3Wci7tay2IHdk7Uo/N1qpcUzX149gMithi4tVrRwVB8zZhbHoi/Xn5qFUdTbqqBW2FTG8Nn4idenzwy3HXl7xOk4SLfuu33jXa708UOrD7zNafztbMVZ4kvofj6yZcGfy+3TRq05UXFkRx3ntpNhzXFWCCb5HIm+7cbBnpp70DXD6OpMl+zHV5f+tCtaWfkXpWZoJeflm65f/izk3fHX/ee035vltiB+PpfeWfXNLED0kzF13/yq5/Un/sPj+q3Px0PTnr+6r5OH11dxECe7Ausw5oNVWy75y7f1N2njyjwOyqWEDsQhoFuO7GjC+nArerLNxeT89Es3aMrzWrPePHqgd78d96u//mH36d//PZP6scffUaXb/Y3svgqKT2/7NUsNmoaT2ReBv2733lKktKYzKPbHf2hN929jsOqNYqvNeJvmsKRztfbTuxoqxOMF18vPTG48ViDQefrdAO36HxFZaLDeCv/xMzXGhRfo+kH0zXx4TlKHrY6U2S+1mX7UiP098uLr6fukcIt6fKTqzumIsQOTM0P1BrNG7zj1K4e/9tfq/vOHB0q8q3bTJ2vK8t89bEDOZmvUtz9WnHx9ZVrh+nDraTpc/VMcVf4Had29eJVBm5tqpf2Bnnbp45sKbJO1w6iqYqZt2S+f77oVWfV7YQ6tt2p7uHduUHna5bvfL16Ps18naZYvPzO1+piB/7bYy9Kkl5KBsQ8e2lfv/+z79Q/+COfrT/xhffpL7/tNfpTX3R/2S9RudffdUrf8tb7JElXbm5egabJzl/ej+MB/Y6KJXS+StLtp3Z18Vpy7VpCJ+HFpLB7ZlIOeUa4pqaJH33vM7p+GOm/f+IVSdJ//VAcn5U3cGsT+J1Mm7i2P/3ydXXDQG975Lahz//Im+/Rh/7m16TDQTFA8bVGfOdrMNKxFIaB7jx1ZBA7IMXFVxuttWspHbhV9oCfiR3guQCV8R2tEzNfa1CEmKbzVfN1vr77MxdrN2BnVD/ZprcVll9u1rl9qZGig/zOPi/sSKfvky7Vofh6OEXxldgBaXCfkDdp+9hOV6+9/Xitiq/7faudKTpfVzq4o38j/lpYfL1F2q82V9F3I//9P/JG/dNvftNUBTZJ8cu7gmvHXaeOJLEDzX1512QvJ1uI3/qqM/qLX/Wa9PNpvje2khifW45uabsb//jkka305czCbl6MO8RHO193T8X3XXvndRDNnvla+RqvOHbg+mGkJy/E54dnL9/U1f2+ru73dd+Zo/pjn3+v/u43vVHf8TUP63//xjcseuQz2e6G+v4/9EYd2+5sZIGmyZ67vK97bjk6eKn3xDukX/7eyl+G3XFyV6+sInZgloFba+h8tdbpR9/7TNotutUJ9JHzcdb1rRuY+SpJp4/Gx13357k8T7x8Q/edPao/8Dl3Shp8/7zh7pPpdQrD+FOpkb39vk7sdOKtCyMPzfeeOaJnLt0cfHDutfHXNQ7dCm1PRqHUKQmdp/iKZZim+Fq7ztdpYgemXyQ3e5H+x3/9Hv3wu56a/9hWwMcOTBq4ta7tS401qfNViqMHahE7ME3nK8VXSdrb97ED+Z1eD91+Qk9euJG+9Fi32TpfazBwS5KOnKm88/XD569Ikn7P627XH/rcGbbhmcPCXRN3nNrVK9cP1TPJnxvrY6O8fO1QZ49t68e+7Yv0BQ8OhlpNs14k6Vf+X1+ud3zHV6Y/P7m7Vd3D+/6V+OvRs8OfB0EcPbB3fhA7ME2sSBprv6yBW9MUXyf/3v/twy+kP37m0k09mzx33XtLwYuaFTt9dFtX9nuT/8WWuH4Y6crN9f153OxFunijp3tuOTJ4qSdJ7/oX0sd+rtLf6+7TR/TSnu98rb58c+FG3Cgya+brqt/5vbh3oJevHeqv/d7X6jt+72v1fb//s9J/tqldlv5l+kYWX1+5rlffelxf9/o79a1f+qD+tz8Q/3285f4zE/6f7bW6UY2YaG+/r7O7gXToxh6aHzh7TL/w2OCmQOcekhRI598vPfL7VnugicD0FAVbKr3tSi4QHdn2TTK/cVE6NnLjevOSdO1F6fbPyv//YDq95CanNPP1uGT7cURBWeFz2WaI55jFxes9Gev03OUKB2wsQT8pDGxNiB1Y1/alxooOyztfJenMg9L5R1dzPGVM/kT3IUEoOvsysQNH8m/fXnv7cfWN05MXbui1t59Y5aHlOugb7Xan6IxbaexAycAtKe58vfpspb/lOz95QY/ccWKmSdKSkjzk/P/Pm+49LeekJ165qddJxA5smJf3DnRrsk3WTzOXptvGL2lsfZ880k1fziysLBf55F1x7MBJo+1OONXgKf9vVP4tWmHsgHNO/+HdT+m1tx/X6SPbejZbfD1Tj+LrqSNbukrna+p7fvrDev7Kvn7mL0wxvHAJ/I7Ue7KxA5J05tXSO75fet0fqCwi4L6zR9WPjNTRkmIHejq63dHR7elLQ+Eamib8mnzw3DF92UO3qm+sIuP08B0n9Ma7T630WKqSxg5s2IuVvYO+nrp4Q1/9utt1ZLuTFsLffN8ttTln1hGdrzVydb+vW3eTm4ORG54Hzx3TlZv9QUD/7knpwS+XHvvJtd1whzYuvpZKLxBudVsK6+CZd0v/8NXS8x8c/vzt3yf9669eyjCPVkmLr2Wdr8mDybq7X6Ok+FpaAJ49dsDnBz5/9WDCv7levvO1O2n7CZ2v1Yqm6Xx9UDq4Gr8UWqepB27R2VcWOyBJ952JC4pDGfFrtD9152uwuhe0vZtS2C0u2By5pdI1ceMw0qNPX9JXvPbW2f6PJoq/5wuuHV/4qjPa6gT66At7ySecPzfJy9cOdXsyeO3M0W1tJ9fIaYuvo07uVhg7UJaLfCrufL1+EOnYznTHGibPApWv8ak7XyfvnHj8+T195PyevuWt9+u+s0f1zKWbeuenL6gTBrr/bD0KCaePbunKBnbHLcvvPnVJH31hr7Sj+uMv7imqeCfIuz9zUcY6Pf58fO69+/SReM184bdL33dB+vLvlC58Qnr6dyr7Pe+95agGLQrLyXydpevVH8Wqn+2fSwve8Zrc6oT6n770QX3Ja86lg/02zSZ1vv73T7ysj5y/qqv7fX3nT3xI1klf/4Y7hv4dCq/lKL7WyN5BX2d34208eZ2vkvTkxcy2hjf9iTgQ/5l3reoQh3SmKb4mF4hArl3DdJ55lyQnfepX4p9/8lekH3qb9MlfjjsKPvyTaz28jXeYZBr+3+xdZZgb19k9I4ZdSbta5rXXjDE74DBDgw1jkzRNOaW0Tblpv3LTNk2bpmHmNAxOnMTM7LW9XmYUszTfjzsg7QpmpBHsWud5/IxWMBpLmrn3nve856gTeL4C2fd9FbI4SMJ2gDXH77fmBskSC2z7cyLbgWy0L01p+CODG6PCVEu2tp70H08ssARTnnwVBDZQZ3zgFotSRlnJ+rdlGx5/UGAaegYXcX43oIzTNaErBjwWICTN721r+yj8QRprRJOv8bsmdCoFltYX4WAfU2A8nuZYUwCDNi/KGOWrTEahzEBuqwV4qEaDpJ6vnPI1yiLaUAM4BmF3uiKCv+KBneJI7/nK/H8lUL5+dGgAFAVcuKASdcU6DNi8eHZLJ65fWYfCGNfbTKNIp8pqm326EQiG8Lv3mgUVDwftHgzYvPD4Qxi0e6M+Z8DmwQUPfI63GDsJ1s9XKL75/C48tbkj4r6tbaO45uHNePizVvzizQOYWV6ABTVGYjug1JHf4txLAbUR2PmEqPeLh9piLU+5psF2YMTpg1lE2BaQ4aIpg64xFygKqDIlmN9OImiUMqgUspxXtdM0jXte3IPfvdeMy/+5AR8cHMC9583GolpTtg9tUiFPvuYQrG4/zOroyteGErJQaA8fOGaeR7ZdWzNxeBMgC/kRpARUm5Gd6lhW0b+fbFvXke3mB4GeHYBziChudj+TtUObEhBiO8CqYp3D6T+eeBCifA1TiAsFq3zts+S28jUQEmY7QK4Rx9NFIs3wuwBFAtsBLePJlE0lPluckCVodcuTrwDIPEEho6CLoSZllStscSaboGkaHn9IIPlKZdDz1RnfkkNbRH5rXlvs54hABzNvm10h0gZCwNixapoZnaz1TP78mDQIhmgMOXjlKwBUMtYDyStfpbQdiOOLXFgOgEbAPoQinTDylVO+psN2gJKTAMl4iDF+0DQvDPmkeRCLa00wF6gxs5zMHysMGnzrrJkSH3TyMOok9PXNQWxtG8VD647hF/87gE+PDHGdUwD5ruxMcWFjyzDueHIH91h7DFK1x+JGiCbbHR1jOP2P67C/xyr4eD46OIDNrSMR9727nxC5f/noCMZcfvzjuiVQUyESgs0WK1Q6YOY5QPsGwe+VCDVFOsjA/IbToPAcdvhQIlb5SlFS1SgFo2vUjfJCjcAgz8kBiqKIpUiOn9sDNi9GnT5saRvFsSEn7rtwDu5YMy3bhzXpkCdfcwg2dwBFyujK17piHWTUuAFGayLqDcdA5g4yDPKQD0GZMNsBCvTUUrXRNPDgKuDzPwM7ngCGj5JWxje+CowcAwYOkOd1bSVEYXh7/LzLyPPzRFPyEOr5ChCbh56d6T+mWOCUr9LaDowy5KvdG+AmpLkIH5OIrJLHnyjJ8sJXaeGxkDEiHnQM+ZpN24EQ89tN6Ms8BQO3aBpoWQuEgoJfYvP4YdAqY7bX6VRyaJQyrjiTTXhFpaFn0vN1YqhpBLRFZOtO7bywuv24/+2D6BpzQy6jBBNVHASo+qaXFoCG+OJdHtlFc78NwRCN8jCv1woj+U0KDdwaD4NWCbvHj5AUSod4ylc9UXBTTuHkKwvJC6xBn0BP/4njRyhEo/GH7+BPHxxBv9WDPd1WnDm7DABwztwKvPX1k7Hh3jNQLCb9Pc0waZWwuPxTtpOQ7e7c2j6Kmx/digfWHuUee3pLJ1b9Zi0G7R78+PX92NNl4R7rGHGN3xUAYIhRxI44fJzqNSK8Og48/iCcviDXbQIQAviDA2TN7QuEsKDaSLyXuTVJ2PlirAUc/ZJ1UGiU8rT+FkccXtHKVyqTQZkMusdcqC2enMFa8TAZyNdDjMURu65b2WiO9/Q8YiBPvuYQrG4/ilTMImzcwkClkGFaaQEe39iOdYcH+QcKK0iAUxagoH0IyhINBGRRIAM9tVRtHRuBoUPA2l8Ab34D+McyoPktYNfThJAdPgLUriLEwuF3SXiHeQZwxX+BykVEeePNcjv8ZIaPabOM6/ka9hirQM4GOPWSgMCtJGwHANJalavwBsg1TZ0gdIeiqKl1jZAYoia4oSDgsQEaU/znSUQypQSWYEpYyJNNPW6pYwPw9OXAkfcEv8TqDsCgUZBAR//E856iKJj1agzngPLV62fIVwEKlYwG7vnd8Qt3bMJ7ikWJP31wGP/5vA1PbmpHsV4lKJgoAqHE50ZjiR4hrng31U6QqQmapvGzNw6gSKfEhQsquftTVb4atUqEaMDpk0D9Gi9wiyFfFZ4RFOmEtePL0uXFGPQnthwAmPEj8vxw+8nc5B+ftOCxjW2QUcAli6oBEBuI+dXGhHZJmYZJp0QgRMPpE16wm0xgPVRdXvL/e29/H9YdHsSW1hG8vL0LTl8Qr+zowRhjvTCvygCFjML3X9mLP394ZML+2HFw1OnFoJ2Ml0K7QtgCps0TwD0v7sYnzYNoG3aix+LGCXUmAMD5Cxivy2hKcUMVUcM6h4R/AAlQyViTbGodxYcHpRNehUI0Rp0+0Z6vmRBNWF1+rqhE0yRkmPV7nUpgCyu5hs4RF/Z1E7U47y8PqOQyzBLbzZMHgDz5mjPwBUJw+4MwxlC+AsA/rjsBGqUcz23t5O/MKvnqT0y+sspXKtOuMGnCloeBbf8Fdj018bFX7yDb3U8DdBBYeSdgrCOErKULaDwFWHAlUMAM1ln63qYEhJCvJTOBmuXk9uCh9B9TLHC+fQJsB5II3AKA3hy2HmDVb4l87ChKMoHAlEPLoAOzfvIemvsFtkF7rABonlyNBW0OKF8l9OybdGDDOIYnLhpjweb2k3CGh08DPv2/qM8pKVBhOAc8X9nCiypB4QVgPV8zFbiVwHZAV0K2SVrW2D1+XPvwZm6u5g/SKCkQpygCIOjcaCzR88rXPPk6KTDs8GF7xxjuXDM9QsnGWhAIsemIBtYHWhL1VLzALeb8UHtHxHu+Su0/JiSsEYg6frjCCMxnN3figgWVqMuRYK1YMGnJ/3UsBzob0gGWfPUxWQFHBhy45bFtuPrhzdjTbYWMAn73XjMsLj/uv2w+3vjqSZy11d/CVLIsOOWr04dBG7ktdGxkSdpBmwev7uzBrY9vw5EBsva45+yZuHJpDa5ayvjmc8WKsKJeIVNYsfcJ/N8nRpWRjCNv7x/AExvbJduvzeNHIETDLHKcopB+0cQZf1qHFfevxXkPfIZvv7AbvVY3GkviFE8nKYr1Kow4s180H4/zHvgMF/9jPUIhGgd7bTAz1/w5VQZBc7s8JiL/qeUIWJN8o4KpWEeZ8MyuMGBhjSmyvaKwQtILuxgoaB9CApWv1FRQvnqswLvfA96+Bzj2ceRjpbPJtnIx//fM80koWusnRFlmrCGPFbLka3a+tykBnxMAlWABXQzc/hH5Hvr2ZOzQJiDATPTiKV+TaBsddfo41cmxIUdyx5YBsOq3RP5MVBrSW6cKdnaMwRcIYW+XQK8yj4VsE9kOKDVkrMkFz9eE5OsUtB3o2kK2o22CX2Lz+FGm9gPWTt5bfBzMBeqc8HzlCi8CJugyisqw7UAckkXPKl+TI18P9dmxqXUE/iD/HxLrpQeAqKaAuMpXvVoBE6c+nORzrOMEbKdKY0nkb3BBtREapQwVxuSCZAxa4pstie9rXOUrIV8NIat4z9fUjywSKZCv7jDy1e4N4IvLaqU+Oslh1E2eVHShCIZo/OLNA/juS3twqHdigfnsueVcmvqPLpjD3b+0vggKuQw3rqrn7hsKC97a3j6K1iFiBzDi8HHn3cE+G37zziF4/PHVw1yugpUXN7QMko7FJXVF+ONVi1DKBOZFtR0wSE++ssrXUZdf0u4WlpAWO07JJgrKJUUwRGPE6YPbH8SRAQde390LmgYuWliZ+MWTDGUGdczguGyCLVId7LPhYJ8NyxqKsKKxGOfMLc/ykU1eJEi4yCNTYD1lCjnyNfrkq8Gsw/qWIdA0TTzfCiuJ5ytNp8WAOx6UtB8heQLflbBExsnOvWL/K/xtxwDQdBbQ8hFQUA7ctQE4+Dow4xygfx9QvYRMWudfwauTjHVky1VD88rXpMH66Ar5zVcuAo6+z7wmC9VSQcrXZGwHfFhQY8KY04cH1h7FBQsqI8I7cgWs+i2R72M2vKMmC44yE36hXmVwW8g2kfKVfU42yVeWYEq0gJ5q5GsoBHRtI7fb1wMv3Ahc9Fee+IuBMacPS0sYpfJYe9TnmPUqHIyyiM00OMsRQYFbGVS++l3xz40Ula+jUdQrpckoXznyNf7nV1aoBcYwBSZZxwfY9ueyceP1isZiHPzFeeLtKRiwylebFB7wrPI1ShceNEbQMiXMlE2w7QD7P5Le8zV52wGXnyeplXIKyxuKpT22NMCkJf/XXGxPThb/+LgFj21oh1mvwqyKQmiUMmxrH8P0Uj3uOGUaLj2hGmqFDDZ3AEadEp8eGcLOjjHMKCMtz7+6dD4uWVyFq/61CXu6LHB4A6gwanDdfzZzQc+jTh83B2Xb9WeWF+LKpTURx8KtrUHm2ONxqN+OapMWevU4+iSa7QC71rP1pvLxRKCCIV9DNMXlPkgBtlgr3vOVSmuYdvcYP+ctN6gxYPNieUMRppXG6XqcpCgr1MDi8sMbCOZUmJiMIoHp7+3vR/uIE5cursY3z5qR7cOa1MgrX3MEbBWzUM5MBmKkVNebdfD4Q3x1pKCcLCQkSuUVikAwBCUCoAXaDshAT35i5dCbkX/PvZRsKxYAcgWxFNAYgIaT+AG4NCwl1cRU1QuZalFe+Zo8fA4+UCsRqhYT0qZ3dzqPKDY45au0tgOjTpJM+perF8Pi8uO1XT0pHGT6wKvfEilf87otFs9s6cCRATu6x1wIhWgcHSTKZuHkK0OmJvJ8BYj1wLGPgVe/DAQlSsoWA1b5KktQC6ZkmFK/kLE2wGslRZnRY8Ch/wG7niSPHX4XeOKSCT4cNE2jz+pBk4r5fi0dUb06zAVqjDi9oGkaVrcfG1qSIxFThZcL2xMSuJVJ5asrUqE0Hio9IZ2SVL6y6qv/u3wBFteaAAAlhemxHQCAMiM7X5xC58cUBtv+HK1YmizxCpDALQARAUFJw+8i6xBZlHOXohDQmmGGDSaBylcqXc4YKShfnV5e+XhCbVHSQWeZBPt5W9xTw3bAGwjioU9bcMGCCmy/7yy8+fWTceYcskZqMOtxzYo6aJRykgbPEP1P3LoCm350ZoQf7/wq4s/72MY2fOuF3bjm4c0RpOCI04sBW2RR7NktHQCAg702vLi9CwDw49f34+TffYzvvrQH/1zXMuF4Pzo4gBnlUdYefkb5Gm47oC8jvzsJ13rlDPlKg5CvUtl4sCpfsZ6vJCgzfeMOa/Pwg/Nm48nbVuKnF82NUD9PJZQxc4ShLKpfA8EQF0zH/s3i4c9aQdPAnMq8z2uqyJOvOQKWfNXJmElTDOVrvZlc2NvZk4NTUUpnvC0EvmAIKvhBx01wB8JtByb9smDoCFA8jf+74SSgeilRu8ZDzQqyNTHKV3UhoCrMK19TgdchXMVatxqg5BOtIjIFTvkqne0ATdMYcXph1qvQVFaAxhI9trdnUb0YB0IDtzLadpyj2Nttwd5uC3782n6c85fPcPLvPsGL27twdEAk+crZDghQvuqKyOJg7/OEEMw0OIIpUSFvinm+OpjgzMpF/H07nyTsRNvnQNun/KKtdzdw9ENYew7DHBhErZxRvgZ9gH2iqqakQAV/kIbNE8A/17Xg+ke24JPwoM4MQajfM8AEd2RM+eqOb1lDUUT96hxJavdDdi9kFHDVslrUFJH3Sc52QFgYXbGezBf9gSwUT/IQDZYESkoNHQes/+qIFIo4vztugcKrKoaZsglOX2fVhJKf40G/QPJ1YudEuO3AiU2TI7WbtRiZKsrXvd1WePwhfGFxNfcbYUmoKlP0a7RMRnEqbxZalRyrphVjQ0v0a7Y/SKPH4o64b2enBRuPDePWx7fi+y/vxbb2UTy7pRPdY268vKObsywIhzcQwszyKORTNOWrXEEEUjbpyNeKQvJbpwEEQrQ0KneEKV9FB26lNyiT7fq6flUdZlUU4raTG3FCnYB57SQEW4zLpvXAi9u7cfafP+W6M4YdPoRooLRQzfkwz60yZO34pgry5GuOwOYhk2Y9S77GUL42MOQr5/uaJRWlLxCCCgHQQlpFMck9Xx2DpD3U1g3MuoDcJ1cDpnrgjo+BlV+O//rrXwSufIwkX7IorAB6tgOWztivyyM2fCLIV62JBG8dW5vWQ4qJADOQxlW+srYDwsglly8Ijz/EmeMvrS/Cjo7RnFSXc56vQgK3cvD4MwWapnHJPzbgkn9siLj/nf396LG4QVFJKF8Teb4CfOgWAAxPDKxIO47XwC0Xs0g0TydbSg6MthILAvYxlgx/5krgmSthemQl/qp6EJV0GJEaxXqADXdae2gADmZu8as3D2b8+sD7PQsN3Er3ETHwOSIVStGgN8dVvn7SPIiNx8jjNE3j9ie24919ZB425PChWK+CXEZxBEJygVusJUd8VThLyFhdU0MNN9UxYPegWK+SPKyEJXNZb8uUkMAX2aUsRjU1jNKAcBFBWpLRgz4RtgPjA7fI+fXTi+bijlOmRXtVzsGonVqer5uPjYCigJWN/DyEJaFika+x8J+bluFXl87HHac0xnyOglHLrplZCpVchtse34Yxpx8mnRI3/XcrAOAvVy/CPWfPjLmPk5tKJt7pY+Zm49clhZWSrs/ZIh4bsihJoQW852uxQCU7i3TP248OOFBp1Ewg26ciWP/gQVv2yNfdXWMIhGgu+K6fGUvuOnU695xqkedlHhORJ19zBBZm0qwDcyGNoXytMmmgkFFonaB8zayK0hsIQU35E4QIgSOVSGtC+o8rLfjwp8B/zyK3a5YD+lKgZEZCHzYO2iJg/uXj7qSB7m3Ak1+Q9FCPGzgGSEVZKJrOJOqxJJVMKYELFIpzrnA9ecJ2yXo9saqTZfVFGHP5cSxKpT6r8LuF2w6kY2E2idA9xqsyCjUKHL3/fFyyqAqfHRkCACytK8Ko0we7EKUD6/kqyHYgTEUwkgXyNSSQfMUU8Xz12oFQkCdYF1xFtre8DWiMwM4neNJvrJ083znEvXw21YUi/wDvIR2FfD2pqQSNJXp856U9ONhHJtGtw07uXMwUWKWEEP8yoqDJwBWApslnqkmg3tCVANZuoO2zqJOX/3u3GX/9kJwv/TYPPjo0gP/tISrkIbuXI1srmfCkpMhXgcpXI7NgHsuTr5MCgzYvp+6TEiqFDCUFqgnt1UnB74qrDrfLjZgt60LjM6ujWp9EA/GHlFr5mrztABskc9qs0okenjkKjVIOrVLOrRknO7a0jWJ2hSHCvqKuWAeKAprKxPl66lQK3LiqniOKWMuX8LwBdp9L64pwwYIKePwhfP+8Wbj3vNlwMwFcJzeVYvX0SCW0QkbhwC/OxdH7z8eamaUT35yzHRhXsCidTdZ6HmmsAdl6TYghX4clUkmOOL0o0imhEGARFA4ZRUlmfRANx4Ycon8HkxVljKUEqzrNBpr7idK4uY9s+5mwuZWNxSjSKTGjrIBTqOeRPPLka46ge8wNlUIGnYz1h4w+6VHIZZhbZcCODqbtsJAkQMKRWfLVFwhBDX/8ECEAbDu1DKHJq2rr2cHfLpkJLLya+LumAnbBPdpKFuJ5iIO9n//tC0HlIgB0dtqqA16yOIg3YHHBdMLOEc6fiSFfF9eZAIAjWnICXgfw21osO3A/AEb95rGR33vnlglPp45z24Hw725lYzGUchmWNfDE6I2rSaKvIPWrx0LGkBhFvAiEwlqVRyZ6nKUdnOdrIuXrFCBfAz7grwuBrf8B3MwYXrcK+LkVqF9NxpaD/+MJ1dE2/ly58XUcaLgFavhR4O4Fqk7g1bI0DWx5GHCRfZYWqvHbyxeApoF93Vbu7R3ezLale/3CLEeADCpffU7yO1In8C3TlwCDB4EnLgaeu3YCAdtndXOLJHahspf5rIccXk7FMqfSALmMQmNJEmGPAlXhRiYkZaoQMlMdg3ZP2sIxywo1+OzIEBrufRutQ47kd5TAmoP2hRV6o1ifRAOxFkn+kKJCsO0AT76yHQAs+apTTQ7ilYVJp5wStgOhEI3dXRYsq49sI68t1uHj75yGs+aUJbVfc4Eaf7v2BDxwzWL8/sqF+NcNS7nHLl5EOhAbS/X44QVzcP9l83HbSY24enktLlhQgZWNxSgtVGNBtTFin0V6FfRqBZSxyEl7PwBqotXTijtIJsuOx5L6v0wA8xueX20CAFz98GY88FHqRfMRh4/rpBODdIkmrG4/Bm0etA07uY7fqQ6zXg0ZlT3lazBE4zBDvh7qs6FjxIn/fN4KgKjRN957Jv73tZOzcmxTDXnyNRdg7cbKw7/DNJMCsmMfA+amuG1mJ04vwa5OC5zeAFlAKPVZUb6q4I+ehBqOMMJpUhIrXkdkK27xNODc+4GTv53afk+7F/jCg+R2jMTqPGIgGCBWEKzqWwj0bHr1UPznpQNBn+AihVByifdnYtRVBrJIGpSi3VAq9O4CQn7M63kRi6gWqIf2A/9XS9Tej55DfC39bmCwGUD6jftzHQd7bZBRwJdObsRtJ5O2uWX1pBXvmuW1XLJvuBl+TLjHhFkOAJFJvMPZIF9FeL5OdoweI6Rr5yaifFVoIpUyjWuIRzRLgo+1Ae2fE2K6dgV6UAI15Ydi6AAZi8xN5PwZPgK8+z1g/yvcrqqYEKZAGKPJWhBkCrzqXQj5mqHiCxtOqk6kfA1TPh15F/DwJLbTG4DNE8CAjYSaHeon++yxuDHq9GHY7uVawFdNM2PHfWehtjhOwFcssIXZBGF0RTqGfHXm0PU/j5gYsHnSonwFgAqjhvO2XHc4hfmOzxnXduCjkhtwAEyrvkC7GgppSEYXaTvg9AZwxp8+xV8+PMLZDkyGoK1wGLVKWCa57cD+His2HhuBwxuI6iHZWKJPSWF3yaIq1Jv1+OKyWpzcVILvnD0TG+49AyfUmUBRwNzKQpQbNLh+ZT1kMgoUReHB65bg+TtXASAK41tObMCda8hv3JzI27hvLxmPx/skVy8h2SDN7yT9f4kAc/7cehJvrbDhWOqBmiMOX+L/YxSkKyjzsn9uwIrfrIXdE0BDMoXLSQi5jEJJgTprytf2EdIdJZdRONRnwzee24UdHcTCzKxXQauST7prZa5iCqxmpgA+/R3OtL6Gb8ueB7q3Asu+FPfpJ043IxCisa09TP2aYfKV9XylEtkOhAduTUZeZWA/Iup6QpRkQlE6m2yHDku3z+MBjgEAtDjlq55pE8oG+RrwCrDnEBcFPF75atAqoFbIsmrUHoHWdUDzW9yf5yu2Q2FlVMftn5Pt538C/roA+OdKwOuIrKAPNmeHCMwiDvbZMK20AD+5aC5OnE6KBXOrDHjujlX45Rfmc8q5aCEQE+C2CAvbAoCTvgmojcCci7NjO8CRr4nUR+mKy84ghkihAQMHANcY8dsNX2CyoYwsRtuAvt1A+TxApUeHn5DxVMANVMwHyuYAgweAMZLaDCe/CCs38uQOm5CcceWrQMsRIIPFFy9RdiS0HWBUxKhaQrZhRQrWB83tD8LuDXDKV4CE5oUrXwEIToSfAM52IP65YdCS/R83nq9d20g43SSEPxjCsMOXNuUre64DQEEqrfQJlK97Q9PwC/195A+BHRNkjM+u7cDP/3cAbcNOPLGpPUz5OrkIBZNOCeskVr7+8f3DuOjv63Hjo6SrY25legN8FHIZvn7mDFSbtFg9zYz1PzgDTWUTOx8oioogfH9+yTzOwqAo0TW8b09keGY4TPUSrj3I+VMQ5oHa3GdLeewcdfkEh+eFI11BmeHz3AZzEoXLSYpygwZ91uyQrxtbyPzxtJmlODrowB6mk2d+tQEyWd5qQErkydccAM2o4s62vUYqzYuvi/v85Q3F0ChleHRDO/FayQb5GiTKVypeiBAQ5vlKZ8bPTWr07SHbuzYA39on7b5LGEP3oUPS7neqg/2tF1bFf144dKzyNfUKsWgEvYmVr9yET9g5Mt7zlaIolBnU0gRtpIpggKhbt/wLMNWjVz8HS2QtfCABQL6P1k/4CelQM2QUhWtCbwP/+wbw5CXAizdl5/izgBGHF5tbR7BwXKsbAKyeboZKIYNWJUe1SSusldRtEeb3CgDTTgV+2EkWDs4hPiAuUxDiiQyILlDkJIaOkO3oMRLgqIv0lZtIvrYCg4cI+QrgsNfEP1axkNw/1k7a44GIBZ5aIed8Rtm2vUyTrz6GfBUSLJTu1GQOHoHK12mnku3Ku8g2rLV6IGxxNGjzoLnfhhWNxVApZPjK0zvhC4SS83gdD4G2A6xP33FjO7DtEeCD+7J9FEmhY8SJYIjGtNL0qLnCSV2LO4XfQ4LArWGHj3QfqQqEK1/TZjuQWPlKUxQsLi9e2tENgJBpLl8QKrksdit5jsKkVaX23WYRbl8Qj24ghXiaJuTdrIoEFjASgqIoUYFBBg0pYBQXxJmfuEbJeF65MPrj+lLp1h7MCaQIK1bbPAH0pkjYWd1+LrhRDDJhF1R/nNgOAMCM8gLOdzWT2N9jxe/eO4xl9UX42cXzuPtfvms1Xr/7pIwfz1TH5Bpxpih81gEAgAxB4vmWoF1Uq5Ljvgvn4rMjQ3hhexdDvkqXpigEPp8PcooWQL6yytcMJhlLBZoG9r0MGOvIInf8wjhVaAyAoSavfBUL9rcuRvmq0pFFQjbI14AvsfIVgJhAoRGHFxqlLEKxUVaoyWpKJgdLB39bqUOnbh4WUMf4gKFpp5NwoTPuA659gdz39ndw+5G7cDf9PAkccgwQRd/Awcwffxbwh/cPw+0L4iunTY/7vGml+sShaqEQaVcviBIKEQ8sGeVNwScwGQgMFeKUr5OtiHf0I6LUA4Bh5lpPh4COTYCuOPK5GhP/PdQsJ969jgGuS2KHJSx4omIBUDaXeY8PyHacuoYNe2JV05m3HRDr+ZoJ5atA8nXRtcCP+4knLwDY+DlWuDKlZdCBlkEHVk8z48nbVmDVtGJUGTU4gfHhTglCzw3qOCNfnUOMf/jk84A+MkCurzPL00M4hZOvY6moIxMEbo04vCgpVJNWa4EdEzKKkl4lx3rqx8DTmzvwg5f3os/mw9bWYZj1Kly3sg49FjdcvsCkbKOdzJ6va5sH4PIF8ceriEq0sUQPjTJ3vwOFXIYinRKV8ZTqrEinIhb5WgJ4rWQtkCrYNQIFrJ5mxmyGuG5OMe/B5vbDoBFPvqYjKDM8wEtGAbXFwsnyyY75VUYM2b0ZtZBrH3bi8oc2okCtwF+uXow6sw4PXLMYZ80px5K6ItEhbHkkRv4TzSJ6LW6c99fPcKj5AACABkXMuQXg+pV1aCzR4/0D/aT67BjIqCLI7yOeUjKlMHWHDKHJ5+fYspbYQJzy7fhhSamgbA7QL7Gidirjsz8CL1xPbovxfAWIyiwrnq8ClK8A0xYn3HbArFdHtEiVG7LnFRQBVgWjNgBn/hRt6jnQwkt8LkEBN7wKlM0G1nwPmHEOIcX7dqPOuQ8FcAN1JwJNZ5PPY+/zWf2vZAIDNg9e3tGNG1bVY0aCBfn00gK0DjniX0vbPgVsPcCcS8QdiIoh9nwZrroLVPdNWuXrM1cA/z2L3B46QrxaAXJdGE++UhRgrCW3513G3182F1a3H20OBbzyAqCogRRpyxnytWMD2Y4rLrHka32WlK+c7YBSmPI1nanJHDjyNQH5RVGEfGLHmSi2AwDw5p4+hGiiUF81zYzHbl2BjT88E8saisfvUTyCzPeVUNlHzg2bOweKb5mAcwgATQiNSYbD/XZQFLmWpwMVYSTRoM2Lz44kOedJYDsw7PARdXfJDOG2A0iDCCNB4NbjG9vx0o4u2DwBKCjg6dtXYlZ5IXyBELpGXZPOcgAAjDri+Trp1lQA3t3fj7JCNS47oRpnzi7DGbOTC9XKJJ6+fSXuPr0p9hOsXWRrjlE8ZzMnXFKIP9jvnMJzd67Ci3etBgAc6E2efPX4g/AGQjBoxZOvSIPyddjJj2NVJq0g26KpgvlM99v+3syNbft6rPAFQnjk5mWcN/0XFlfjkZuX5e0G0oQ8+ZpFbGkbQXO/HdXUMF4OrkH/tWu59sJEoCgKp84sxebWEfh1paRK7U2t8iUGAS9ZfMgEBm5NSuXrjseAggpg8Q3pe4/qJcQH0CfAx/F4B00Du57i/2YnNEKhL82S56tQTzLhytdR50R/pqwrX1+8CXjlDl4F8809wOwL0KacQf5uXw9ojIAsbNiRyTj1nktuxFosB259B7jhZWDupcCmB4lCcArj6c0dCNI0bgsLUIiF6aV6OH3BCPInAu/+AHjqUvI5z75I3IGoGTIg08pXoeTrZFW+sqBpQlLMOBfQMwvO8bYDAN9hUbOCt1Ypm4OWQfK9uIpnA/VM4qypgd8XMOH6VsW0VzaWkAm1PVu2AwKVExm1HUjk+cpCoSJjR5jtQL/VAy2j1np7Xx/UCpk0StfxCDHflyzB4pOZZ43YvZOSkImAcyRxgYXtonCPAXtfAvZMniLd0UE76op1aVNczqk0cEWXV3Z246ZHt+LoQBIFNb+bhPlGgS8QgtXth1mvJt7iHmFrD1k6QvXiBG51j7nQMuhAiAb8IaCpTIc5lQbuutgy5JiU5KtJq4IvEILHnzvK76DABd7uTgtWNBZDLqPw31uW48cXzk3zkaWOeVXG+H6o7PpNFaOgImXmBHsCMd0OBo0Si2pNeGN3T9LXfjvTEcNaLIgBBUrygXvAStYxVy6twbfOmintznMcbPjc/p7M8TnDTIAzO27kkX7kydcsonXICa3Mj1LKilNXrUTlrKWiXn/qzFJ4/CF8971Bcod9IA1HGR1BRvkqVwn3fJ1Ui2aPDTj6ITDvUoEt40miagkh3A68ThYdecTGSAvxN2SRaEE6HvpSiSrPIhEUELgFgImcEbTLEYcP5nEeVKWFati9AbiZEImM4+AbwL4XSZiQzsyp+vophiT32qJbqjAFp3/PfRLfpL/HKxwv/iv5zjb+Pf3HnkW8t78fJzeVoE5AqMCiWhMA4MFPWvDtF3ZPXPC0MwrIC/8sPhxQxSy0M10IEuz5ymwnE7kUfqweCxBwA8ZqYOa55D5VFHKDJV/1ZmDaaSSUy1CFlkFCoNiveB646M/kOTIZMP8K/rUxbAfYtGBnxpWvQchllKC2NUr45S81sIFbiWwHwlFYySlfW4cc2HhsGPVh5+vS+qL0qHNEWnLYPT50jLgSPDeH4RwB/jwHOPTmxMeOvA88dDIpZrIKb7cF2PIQsP6vmTzKlHBkwIEZUcJ+pEKFUYNNPzwTKxp55TVbuBGFOLYDY4y9RUmhijwnILDjJh3WInECt9Yd5q+HIcg4cqnKRK6LXaNu6FQphJJlCaw35zef3wV/MPsEbMeIE9N/9A7e2Rff/m7E4UWPxY1FNabMHFim4GPOr1jkq5SZE5ztAK9IvHFVPY4NObGpNbk1pNVNxplklK+yNITo9VkJv3Dz6gZcubRG0n3nOgrUCkwr0WN/T+aUr8MOL+QyKnGoXB6SIU++ZhGtQ04sNZKLdmlNnJaGGFg1zYzppXoM0iZyRwZ9X4N+UimRJVzg82qlSaV8PfwOIc3mXZ7e96lmkpTfuBt47c70vtdkB+treMEfgYv/Jv71+pLseb5KbDsQTfnKer1lxXog3Htvz3OAeQb3pyOkgoNiSCZt0cTXrv4acOm/4FCXRVbuNUag/sQpZ8vxwrZOfOFBQpI6vAG0DDmwrF5Yi/KCaiNqirR4enMnXtvVg16LO/IJ9j5g6S3AgivFH5iKIQQybTvAqfumoPLVF0Z6sL/jgnJg+unktivKYql8HlGcFZQD5/wauPUdWN0BvLW3D0o5heqyEiDcaz2cfPVYInzlLl5UhW+dNQMzywoho7Lg+eoPCfJ7BTIYuOW1AaBiL5SjwVDNeb7+5I396Ld6cMOqejSVkX3cfZr4+ZsgCLbkYIvcSHoBnhOw95J512AUr++uLcDAPhJQGmQ6PDwWUnCwdJCx88OfAbufy+ghC4U/GILd40fbsJPzaUwnisLCc9pGRBbUgn5C/McI3Bqyk8/frFcDCoZ8FeC/K0uHfVcc24EdHWMoN6hRbdKCBoVCFTlPakz8/2syer6yyt0PDg7gmJAAzjRjM3PNeW9//ODnvQyhtKBmYrDopIbPReYvsUQWnPJVWtsBFhctrIRBo8DL27uT2qPNkzz5mo7ALbazq+I4VWLOqzamZCMhFiMOsp7MWwxkDnnyNYs4NuTAYgMzcLI+byKgVcnx/rfW8ORrBluqA35ycZSrhNkOyEBPKsES9r9KwrBqlqf3fQrCWkbzwVvxMXyUKCpX3AEsvVn86/Ul5BzJ9A9RqPJVhO3AmMs3oUpZVkgImf4UU0+Tgns08u+yOdxNbyCIMTnTXq0xTXxtSROw+Fqmgj4OFQsBaydpL50i+MEr+7Cny4IBmwf7uq2gaWBhrbDFCEVRuGAB73U84mSItkNvEeLBNUyIomSQNdsBVvk6BT1f3Rb+djcTulVQRvx4T/omsOb7E19zwg3AN3cTVazeDJTNwU/e2I/Pjw5jRlkh5OMnyDXLgKseJwF2QAShW2XS4ltnzYRMRqFArciK56tQ8pVYE2Xgu/XYiN+rTMT011AJ2HsRDNHY02XF5UtqcMOqejz9pZXYft9ZOHmGSAscoeAKEwnUecy5YdLKOSJkUoI9X2w9Ex9j57dsuA1AxgXnCFFp2nqADX8FXr8LsHSm+0hFYV+3FfN+9j6u+88WBEN0Rsin8PlB+7BI8tXPqKdjiCvYcaekQMWrYwWoX9MSqhfHdqC5347ZFQac3FQCrVoJOUXe26BVQM+QrvpJSL6umVGCn1xE2vVHHNkP2eu1kO8+bms+yHlAUcC8KhFdB5MBPicJ9Y0FKT1fx9kOAIBGKceFCyvx/oF+0Z1vnx8dwhu7yPU2mcAtCtKH6PWMuaGUUzAn+D1NVcyvMqDH4saoM/3ndiAYwrDDS/y788gY8uRrlhAK0WgfcWKanqngs5UxkVDIZaDVzEQugwRF0EeOW5GIfAXr+UpnZmElBdxjwLGPieWAmAVasrj5TRLCQuVPx7jwORKHpMSDvpQsZj0WyQ5JEAICA7cE2g74gyG4fMEJEyVWhZXJiikHO6N4WHQtcNFfgDN/yj3k9YdgYcnXaLYDDCiKmniNqFhAtlNI/couUHZ1WrCn2wIAotrwbjupkQupGGYUSHjhekI8AIChKrkD4wK3suX5mmiiPQmVr+FjcvcOstWXEbLg7F8CRfUTXyOTRxblQNo6AeD3V0ZJU6YoEs5VMov8HaMIW6hRct5umYIvEIJKKPlKZYhX99rFjyOFVYBrBG19w3B4A5z9R4VRk95Fi0g/5FnlBdjdZUnf8aQb7PlijUa+MsRFOPlq6wP8DLF45D3ubnrD3/Clx7dhQ0sWOl2i4Iev7YUvEMI+RvmXibbrIn04+SrSioLzsIzu+TrCeASWFKh58tXvjvrccEju+UrTDPk68RwMBEM4NujArIpC/OrS+ZhRbuCK2xRFYSHzHUxG2wE28wPg/RqziSOMp3A0WxuPP4iWQRIS+v6BfsyuMKAwCZIvp+Fzxu+k0BiJMlYSz9eJtgMAcMmiajh9QXz56R2iBBh//OAIntjUAQAwasWfC1FFEyngk+ZBPLqhDYtqTMetEpMN3TqQ5tCtLa0jaPrxu/jo0CAppOWRMeTZniyh1+qGxx9CtY6pUqlFtMCNg0LPtKxmkFQKMspXRSLbgbDArcnCveLQW6Tlan6aLQdYNK4h4Tj2/kn0IWUBXgffGp0MtMx5kmkVZdAnUPkqzHaAbR02jJsoVZm0qCvWZaft1MH4TS+5CVh2W0SKuzcQgk3BVP6j2Q4wiHqNYMnXvr1Azw7g8LuCFnm5DNYeYneXBZuOjaC2WJtQMRKOCqMGv7p0PoAYC6/Cyon3CQFLSOVq4NakVL6Gk6+s8rVc9G6G7F5cvqSam5RHRYJQjwK1Iiuer0K9UIntQAa+W69VnN8rwBU0jh4jqe6LMtU2K9TzlTk3SgtU6LN4EJpUHk9hYOewA/uB566LJGGjka8jLdzN/s0vkhtFjQi2rcfa5kF8fnQYj65vg8WVPXVgKETjyICD818uLVSj3JB+lVF4yF27WNsBjnyNPt9iFVnFEcrXxOOy5Or2UBAAHbVw1z7igi8YwqzyQqgUMshk8ojOolNmkjlJprsBpAJLluSC8rW5n5Cv4fORQbsHD607hr+tPYoL//Y51h0ewoFeG25aHaXgONnhd8a06ABArs9s513KmGg7AAArG4tx+8mN2HRsGA9/1orD/XYM2Dz49gu7uevfmNM3oSDVEXZtSEb5CokLKq/t6oFJp8J/b05z12kOY14GQrc8/iC++zI/luaVr5lFnnzNEp7dQtqi6gsY8lWM/9g4FOh18FLqyBbHNIP2C1S+hgVuTRrl64FXgaIGEoaVKRiqSHu6azTxc49XpKp8zVZbtVDlq0DpF6tei6YeWDWtGFvbRjO/+GbJ1yjEkjcQhF3FEEPRbAdYRKugF5QB5ibg098D/zkDeO4aYMcTUhxx1sASYK/t6sanR4Zw5RLxljNsO1ZU8jVZ2wEucCvD50fIT8aJhAF6k1z56hwk7eNxChDRQNM0hhxelBUmGGsLmXOPCYYaD71antO2A0iDd1xUeO2ARiz5SgoaPZ3HSCBGafLzNVEIMfNDgbYDZr0SvmAItz+5Hb98M4pvaq6DncM6BoDDbxOfd0sX8MbXACvjZxiDfK0Y2QIbrQUWXwfF8CEY4cDWthH88q2DeHNv5vIQxqPX6oYvEMJNqxsgowhxT6XD+3Qc2HO9UKPAoN0rrvDChdJF/52z+9arFMTzFRBUFKWk9nWOY1nDqjFnsf6644rba2aQOcnOjslpaWTQKCGXURhxZlf56vIFOHJ/JKxN+h8ft+B37zXjn+uOwRsI4XfvNaNQo8BlJyQ5P8ll+JwxVeIcCsqBkWOpvxdnOxB5DZHJKNx30VysmVGKRze04dy/foabH92K13b14IG1RwEAv3//MK5/ZAt2dJB1psXlg8Xl5/aRlOcrd1jSnNlHBx2YX2WAUTfF1NEiYNKpUGXUcNcwqUHTNH7x5kF0jfLX7LzyNbPIk69ZwKDdg/983oorltSgQs1MiFIgX4t0Ktihz6jyNRQQZzsgmywLZucw0PopaePMwASZA6tW2/cSF+yRxzh4bSkpxLPXVu2LDMiJBUoGIcQSa45fqJm4IF893Qyr249D/Rm2HmBtBworJjzkDYTgZMnXOLYDMipG/9LVz5CJ7YKryN+WjtSONctgVUMDNi/KDWrcsaZR9D40SjkK1QoMs6qXcFI7WdsBhZoo7LJxfiQM28LkVL6yY3LpbLLVl4m2srG4/PAHac7TOSaMdeRzDCOkwlGgUcKeYfJVlO1A1OpLGsB6vopBITmnLAPtWFBtnOi7my6wqnCBhYliZsH6MdO6Oekwvitl8CDw0c+BXU+RMC6AJ9w0RuIDH4aDdANQfxIAYLnsMC7sfwgNVB8GsuGDzqCN8Vs9oc6En140F3ecMi0j7zu/mhQYLlpIfrtsgrggcOnt0Qklty8ItUJGzgPOdiCxtQGpL0t4knPkayRxEAzReGtvL2QUMJ0tlFCyCOXr3EoDjFolvnvuLOmOJ4OQySgU61VZVb7SNI1eixs0DSjlFG+DBPIdhKO5344ldUXQKCefx25CJLIdAIC5lwCdmyTI9pjo+RqOc+fxc3BWkfzuvn6sPTQAO7N2+PXbhzBk9+Lj5sGI1ybz3bAhelKc1sEQjWNDDswoT38gYa6jwqhJW3jy39a24Lmtnbjr1Ok4dx4p2ueVr5lFnnzNAg712eEP0vjishoyyVHqU/IWLdKrYEVBZpWvjLm+XKDtACaL8vXI+wAdBOZeKtkund5AYu8xljB57wfACzdI9t5TCl5HSkWKrLVVB7wC/CwBIv1MHLgVj3xdVk/a/Xd1WsQcYepwDJAWxSiLNY8/CJc6sfI1Zkti2Wzg2weAKx4BzDOih7FMEngDQTi8AXzn7JnYeO8ZePPrJyftOVdSqCbKV5rmVUeqQvGqvnCoC7JgOxAQfn4AmJTK19kXkq1c/Hc9yCxoSxORr3IFUNwYk3wtVCvg8PijPpYuiFG+Eu+4TNgO2JK2HQhYejm/14wg5CeEeqJCMPN4sX6Sq4XGCwgGDkYvXGqLCCHuIEW/PmUtArQMDwUvRaDyBIQoOS6Sb8KXZG/iEeWf0DXmwoOftIgOo2Gx7vBg0gthlnydVqLHLSc1YuU0c1L7EYtLF1fjs++djosXkcL+oF2EQpIdA2LMt9z+IHRsUBVHvib+fGRS+zrHsKx5dksH3tnXj2+eORNa9jjHBZrKZBT2/Owc3Hxig4QHlFmY9Sq+AJthBEM0Tvy/j/HXj0gBZG6VEcMOH0euh/uOsrWqjNm1ZBqJArcAYMnNZJ6z88nU3ov7DUcfE86dV4EVDcVc0VOtkKHf5sGXntjOKSl3dVrwhX+sxz0v7om6DzFghyYp1vedoy74AiEuv+J4RmmhGkNirtkCYfP48de1R3DRwkp8/9xZqDSS63dwMvAzUwh58jWDcPkCOOvPn+LJje0AgIYSfXLhD+NQrFdhNKQDnUHlK2s7kNjLcpJ5vnZuJARRRZRgkyTx9OYOXP/IFnx2ZAiPrm/De/v78c914xbI4T6NOZbUmzNI1XaAU76mp5UjJgQrXyHKdiCaP1NNkRZmvSqzoSvdO4At/wJ00dupvYEQXBqmGh8nWDCW8BUAX5wyVMVsq54MGHOSxWJxgQpVJm3iVvI4KClQEfLV7yKWJQBgnp7aAaoKs6N8FUJKTkblq3uMWI5MP5P8LfLa7g0EcXSQXK8SKl8BYtERS/mqVsDpTY58ShZiPF+pTNgO+N3AWHv0oLN40BgQVOpRRo9klkAI+gWEbYFTQRUn0TaaUxgnIKAHD0QvzKy8K6KL4kb6V5jtfRyfBheg1wF4lUY0UMQKp5Iawbv7+vGH9w/j0yPEczEQDOHVnd14ZkviLgqPP4gvPbEd//60Nan/UuuQE3qVPHHxRGJQFIU6s44bY44NObFDaIs96/kaY77l8gWhVY4nXwUoXxElVDMVxFC+bu8YQ5VRg2+eNSPszWWCituTCSUF6qzZDvRa3OizerD2EFFPzqsywBcMwcbMT7vGXFg1rRj/vXkZ5jIelhktXGUSQmwH9CVEPDDWntp7cZav0clXo06JF+9ajTsZhf3dpzXhkZuWAQCODDiwepoZRq0SvRJ1A0hZEj/KkMMz88pXlBVqxBXMBKJzxAWaBi5cUAmZjMLZc4nydU5lCqKNPEQjT75mEPt7bGgZdGBt8yA0ShlZTPkcqbVSg9gOWEJ60C6LNAcqBAGWfJ1inq+dW4DalSkpkceDTbi96dGt+OVbB3HX0zvw+/cOIxAM4ZHPW/HYhrbIdu1xSdd5MPBOZs9XgYFbAqYw8chXiqKwuNaUWfL1tTvJtmRm1Ie9/hBGjPOAq54AZpwdczckCTnB/99QPaltObigEl3q/kpmvZqoXlif6HN+DVz3Ymo7Vemz4/k6FZWvXVuBg/8jKr3qpeS+gom2HPHw67cO4WvP7gIAlBkEEPXmJmC0lfcKDUORnpD16w4PRnlheuAVaTsgaUtyNPTuBkIBMsaLhENVinJqNMPK14AwSw7m3NCrKJ4UmwwYOcYHaQFE+VoyCwPmFXg6cCYo9xgwcIB7eKDuQjIGrP4q551My9VocShx6myiTu4cdcGlMGEaRcYJPeWFL0hIN1a9+pePjuCeF/fgx6/tR6+FdA08uakd33x+F0IhGu/s68N7+8nru8fcCIZoHOoTZuVD0zS8Af78ax12oqFEnxGf12goY8K9fvL6flzx0Eb4AgkIyINvELsHILby1RfkFaVc4FY2lK/RyddDfbaJZMIUJF/NBdmzHWAV3W4/+a2zIUH9Vg/GnD50jboxt9KIM+eUc2TawhpTVo417fC7SAdrIqgLJJhfxbcdYLGKUdgvrS/ifY9BRF93rpkm2TgmRU3cFwihud+Go4Pks8krX4ny1eLyR4wlUqB7jBTJaouJUvukphJsv+8snD4rzztkEnnyNYNgSTgAqCvWkcmY155aKzVIq5kVeoQyGNZEs+RrokUzxXu+5vyS2TkCjBwF6sQvzOLhYIxJe/uIC4983oYnNrZHqlvYYIk8eISCJFE0lXMlG56vNE1UiUKUr0JtB9yxbQcAoi44NuTg7AnSiuEWorRbegvwhX9OeJhdiKqVcmDepXFVXMR2IMH7GSoBe19UcmkygCNf9amTryWFjPLVNULuKGrkQ5eSRVZsB/xTz/PVMQg8fSUw1kZICaUGuOFV4LZ3Be/CGwji9d28xYZg5WvQF1Vhe9vJDWgqK8B3XtyTfpKTgU+07UAasOtp4J3vAz4X0LWF3FcjLkmZpml0+k2oU1i51PqMIBQQ4PcK7tygAFSa+OPL1PecNJ65Elj7S/5v9xhgqsVfqv6Et0KryX09O7iHd1ReA9xzkBRhKxcBAKigFwCFsxgFT8eoE3aZAQYqUolZAitWbfsmRocH8NiGdu57fHR9Gx746Ch+9dZBvLG7F49tbMfdz+zEXU/vxJt7ernF6qE+m6DP89dvH8Ks+96DnyF8jw7Ys6rkKlQroFHy52DceYHPCbx4E7D+z+TvWJ6v/iBvl6MQ4/lKSatuj2I74A0EcWzIidmV4z9zYfOryQSzXo2RaKGbGUAHE7IFkN9YfTH5rZz7189wwq8+hNsfRG0x+W1cs7wOXz51WsbV3xmDz5FY+QqQNUiq86sEtgMsTmoy4/WvnoSTmsyoNGo4n/JygxpfPb0Jb3z1JDx0/RLcf9l81BXrsKTOlNThsEWlVFb4L+3owoV/W4/Pjw6hyqhBgTo5K66pBHa+J7WtSOdoJPkK5P1es4E8+ZpB7A8jX+vNzIU6VTUfGOUrrQfltSZ+slRgK84JSSV2UUDn/kKgeyvZ1q6SbJcuX4CrEAPATavr8R+mBWT90SH02zxoH3GR9Ngf9wNn3EfUH94Mt8bnOljCVArbgUySS9ziQIjtgDBZCKt8jUW+Lq0vAk0DO9rTnOLbtwd4715y+5TvRiX+AiEaIRrCCBghyiBDFfFkdmROvScl2BZBKcjX0gINLC4/3DbSSgudBF6CKimUGSIhtLV6MilfP/09T0awdkBNZwLFwsN2Pj08xJ3rAKAXsiAxN5Ht6MRU5bJCDa5ZXosRpy8tXmLR4A2ESOFFCChKel49FATe+Cqw9d/Aq3cA3duA4umkBVQEPjw4gCPuQjSqrZlVMCZxbjSYeRLAlaTHaUYQCpEiQbiNjNsCaExoH3GiJcSkotNhKlKbnCtg4eR74FSasTk0h/zZVAKVXIbOURcsiJwnGODEPYqXMHN0Hba+9Qg8/iAevnEZKAp4ZH0b/vLREZj1ZIz+v3cPca97YVsXusaIMnbM5RfUBvrf9STo7LMjQ7C6/OizeiKUZ5kGRVERpJfVHYd8HWyO/DtGsdvlC0y0HWh+B9j/aoJjkdjXmVO+8ufI0QEHgiE6ivJVatlt9mEuUMHpCybtZZwK2oZ5sr3MoMbM8gKUFKhx4QLeQq22iBA8KxqL8cPz52T8GDMGIbYDgDSdRexvOKENOOmCoygKCrkMVUxRrjysg+b8BZW4fmU9Pvv+6Xj17pOSOhwpauKH+mwIhmhsbh3Nh20xYK/ZUs/VOkddMGqVME52i6JJjjz5mkHs67FCKSdXqnq26uCTQvmqgpXWQ+538mRPuhEUp3ylKDr35z2dmwGZAqg6QbJdNvfbQdOAgqk6LqkrwpqZJZDLKLy0g1e4NvfZyCS2iEk+z6tfI8ESpqlYdMgVRKWRSc9Xrkghpe2AHzqVHAp59Mv30voiqBSyxCFvqWLd74CWD4mfpak26lO8TIujEN9HGTeJi/MZGJgFub039nNyGGMSKl+XN5K22yNtjMpRV5zyPrOjfPUJ9LWcRMrXri1A4xrg8v8A1zyb1C42HhuBTiXHSU1mlBsEKhNY+xrHUNSHZzIk0OGBzFwDvf6gYOUrRx9K+f12bCDb4ulA89tAy1ryvQgATdOwe/z49MgQ7n5mJ2htMfShTFtyCLQdYFtQaRr3XzYfd51KvJ8d3kCcF2UZ7jHy/2OV+wBojwX7Rilsbh3FMAzwKsh4v1V9Iv4ZuAR/2hXCyb/7GF2jLnhoOU72/R03+n4IgPidTy8rwIEeG0ZDkfOEOmoAZRQpRn7U6sKli6uxoMaIxhKeMOm3ebCwxgh/kPz+TptViqODdnSP8iTTwT4bOkdcWPzLD7CjI3qnWYOZzO2/9MR2fPXZnQCQVfIVQIS3uC0u+cpbPMQLAo5qO7D/ZeCT38Q9Dsn5zyj2Z2zC++yK8R6GFCZF4U4EWPXakQxdz8PRHqZ8LTdoUGbQYPt9Z+HB65fg9pPJOmZaqQBCcrIj4CPXsUSBWwARj/iciZ8XF5zpq6hXsUS44LmEQFDMcaRyXh8b5D+TGXnLAQD8NXvQJo0375UPbcQPX92LrlE3p0jPI3vIk68ZgscfxLEhB86dRxZH00rDVHgSBG5ZwQxynsyoXymhytewdri0h2mkiq4tpJVNyCAqAL0WN+59ZS+UcgqnzyZ+KvOqDFAr5JheqseBXt6OgLMmMDIkVp58jQRbLU6xUJFxcolTZkhnO2D3BGKqXgFAo5RjeUMR1qebfO3bA8y/ErjhlZhP8TJ+YGpl4qGGncTFvU6wwXTWnjhPyl0MO3yQUYBJAs/X5Q3FKNQo0NrBhMZoJSBfsxG4FQqI9HzNcYSCwPARoGwOsPCLwOwLk9pNr8WNmiItnrxtJTbde6awF7HqZ1f0c59tfz4ykJnv2BcU7vkqo1JfxE3AoTcJifTFJwHQQMANrLhD0Evf29+PFfevxXNbOqFTyXHRilmgfI7MWp4E/SLD6EKoNGoxh2m5DldO5xwcJBCLI19DIcBtwSedLDlIYVTTAADYhyb8PnANaMjg8gXx67cP4sODAxjzAn4oUFqoBkVRWNlYjB0dY+gPRM7hLpJvRhllAQAog258mSGn51VFhqddtawWDWYd5lUZsGqaGQM2Lw722VBSoIZKLsNv3zmEBz9pgcXlxzv7+if8l0IhOiLIhh2DZ2edfBWofA3z142n5CO2A+PIVyDmdYeFIF93MWB9ZsPWIfu6LdCp5BHEOgDG8zXXFyHisJrx9dxwLM1zvShoH3GikOnGKB/nR/7jC+fgo3vW8OvcqQwxaxNVQepdjewaIYHn63iw5GsqIa/RwIkmUihstA7z85EZ5cfBb0YAOOWrBLYi/mAI2zvG8NzWLhzotaKuWBqOI4/kkSdfM4SuUZIwd/bccjx+63JcvoRRcEkQuGUuUMNKMxONcWmx6QIlglSiScZpbtsOBHxAz07JLAc8/iDufGo7ei0ePHbLCty0uh5nzC7jJiMnNZG2x2qTFsV6FQ70sORrDdlauyQ5jkkPSyew/i98UUGdYiJjptuqOWWGQOWrgHPE5vGjMErYVjhOnF6C5n57+vzAnCOArZsUK+K04bLKV1UMlW44KCHK1+JphEzZ/BAQzGFiIQbaR5yoLtJy/lupQCmX4fRZZRgYYALImACalJCNwK2gj3QcJMJkUb6OtRNSoHR2Srvps3pQZSK/FZnQ34vGSJSSzuiL8ZICNcx6FY70Z0r5Ktzzlf16JQ3mHGkBSmcBFfOJ4rXpbKB8nqCX7u+1wu0P4uPmQcwsL4RGbyIPeIUFL0mCkEA/5HGFCbY458xl5StLvroZexxLOyjQsNA8UTmorgMAdPv5+2qKtPjw4ADe2deH0kI1Nv/wTLz19ZMBAKumFcPtD6LVSQiGbroE+4vPxl2Kt7BQRuwAKlQezCzVACPHcNHCSiyt56+btUVaPHbrCvzjuiWcAuvzo8OYU1mIh29ain6rBy9sJ3OzaJ0l/TYPfIEQ7r9sPjbeewZ3f4WQsLw0IinyNc66xOUL8rYDijDy1T0Wd1yWWoThdBLFXI+D3+nubisWVBsnjrHU1PN8LS1UY3ZFYfq7nMZhwOZB+7ATp84qBcCHurGgKApNZcdJ+zhrL6QUQGix86tUxjjOdkDcHLLOzCpfpb0W8eN2cq+3e/wYsPHrlLztAIG5QAWKAgZtqa/h2FBJgAhA6s3HgSI9x5EnXzOEjhFyga4r1uG0WWXQsBMXCQK3DBoFnDLmgsX6y6UZsqAXIcgEqzJyXvnav5dYKUgUtvXMlk7s77Hhr1cvxskzSnDKjFI8estybkL4owvm4D83LcOD1y/BtBI9OkaZtovCCqJg2/E44HfHfoPjBe/eC3z0c+DAa+TvFAsVkhjeiwFnzyHU81WY8tUQR/kKAHOZ5NnWYWd6FuD9e8iWCT2JBTZZWYjyla+gx4HGAFz0F6BzI7A/tuI2V9E65MS0Eukq+6fMKIHab0VQZRR2LU4EdSEZkzJJcAZ9IpWvuTyQABhkPCPLUvO467W4UWkU2R5GUUT9yirQnCPAzicjvs8Z5QWZsx0IhARZjgBp+nat3YCRKXRf/4ooC4huxuvTFwxhemkBX/jLpB+7UM/XcYWJAjV5TU7bDrC+3V4bKX5//icEKSXeDa7A7p+ejbJCNfoUpBjd6dVz7bK3ntSIEE3Iz7mVBlQYNRyhsKKRKAEtINdYvakMlbc+BdrI2+JMKwiA2vM88OBKnNuowitfOZGzgakp0qGxRI/GEj1mhJFHtcy8/b4L5wIAKo0aNPfbJ7SEsq3YDWY9qkxaXLKoCpedUJ1Zn+AoKDfGsB1442vEE5nFUJjna5x1SYTtgFwRWTwLs5EYD4qiJD2/e4YJcb+3n8yzfIEQDvXasDhqkvvUsx0AiJBjW/sYN9fKBF7e0Y0QDXzjzBmoKdJicY0pY++dc2BtBIR4vqoLSKcPK15KCsnZDlyzvBZ/vXqx5KFnvO1AcucWm4myvKEIaoUMTXnbAQBEXFFWqI4ItksWLP90xuwyfPecmbjzFOHZA3mkB3nyNUNgE+YiKg7BAFHIpGg7QFEUr3pyRfehkhqyoA9+SqhhM0UCt3J54sMumCsWpLyrQDCExza0YUVDMZfAOx5KuQxnzy3H4loTyo0avvInkwOXPkRaunc8nvKxTGr07QUOv01ub/4n2UphO5BR5avQYDpA6OLALkD5WltESJuvPbsT8372Pjx+iVtl+/aSbYLzxRdkla+JCRh2gZpQ+bbgKkBXAhz7OPFx5hBCIRptw05JfdBWTTOjhLLCoTBJs0NtEVkcZPIcCQamlufrEDOWlM5KehcefxAjTh+qTUmoVPQlhHQFgE9+Dfzv6xGKtiV1RdjXY017SrY3EIQvGOLbkxOAVfdK9vXSNLEnMTDdJAqVsA4EBiz5CgDTy/Sk8AMAnkwqX4NkTpAIXAsqS74SMmxS2A4AgK0H2P0ctpkvgktbAZNOhQK1AkcVJECuLVSGO06ZhtbfXIBFNcQqwOYJTGgtL9ar8J2zZ+K0E4jqvMhcDnOhFtScS7jnlCo8ZL4X8gN2Yh3A+rTWFPHFjuqw29etIArcq5bV4F83LMG/b1wKuYzCl5/eETG2doaJLADgb9eegL9cvTj5z0giXL2sFn+6ihRKI5Svu54Cdj1Nbvs9gHOIV/DFWZdE2A4AkSetM7rfNEAu4VIq211uQkz0Ock8o7nfBl8whEXRyFeS9jXl0FRWAF8ghOE0X8/D8erObqyaVoyZ5YVY/4MzcH5YyNZxB852QEjgFnNOpSIA4ZSv4ugbc4Eal55Qnfz7xgAlRDQRAzRN44VtpJPg15cuwAffXgNDgrXN8YQldUXYJkFwcgfDP91/2Xx87YwZKJIgcyKP1JAnXzOEzlEXCtQKFOnCLixs8E+qhBLAp/cm8FySCjLaBz8l7ASmKRkhX3N54jNylLT3mepT3tW6w0PoHnPjNsZ0PhEqDBr0Wz185XDWecT7tXt7yscyqdFLwiqw5Cb+PkmUr5lULgkMpgMY24HET0vk+QoAVSaycGRJfYtL4iC+sTZCgCYIeWLVGEJ9HwEB5ItMBkw7FWhdl/tEHIP9PVZc+a+NcPuDkvqg1RRpUaVwYCiUoh0HC/b7dKc+4RMMoYFbHHL4Ow8FSbBTUWNKRdU+xjdStPIVIMpXex9Rhu95ntz3zneBp68AaBoXLaxCMETj3f0TPSulRD/zf6gwiiOQJSNnPBbA7+StfESie4wPWiLKV3bhnIu2AwyYzgmWfM1t5WsY+dqzA6CD2EHPRj1DhOrVCuyQL0bXjZvQSlehWK+CTEZx7bMAT5qG4+tnzsBFK+eTP9jr2ek/QnPTnRikTajSeAAL45PNqDRnVRhQbdLyHWkA5DIKv/zCPDx52wrMryaEL0VROG9+JRbWmPDbyxZgV6cF28MWxy2DDqgUMm78zRWYC9S4YmkN1AoZbCwhP/48Y0MsKxaSbQwyiaZpuP1htgMAQIcVd+ORr4Ckl2+vm5yjPXay0/2MfdeCamOUZ09N5WtpgcBU9G2PEFFHCrj7mR34xZsH0D7iwrJ6CTzmpwJ8zDghiHxlnpNK6C/n+ZobHvisaCIZR49PjwzhmS2duO2kRsyqKMy3w4/DisZi9FjcEbYByaBr1AWVQoZyif1+80geefI1Q+gYcaKuWMe3H411AK9+mdxOUfkKAIpCEugUb+IjJeRBH4IilK+ynCdfjxE/SSEqkwR4bVcPzHoVzpxTJuj5FQYN3P4gPykGSDt3ihOlSQ92UrPkFv6+VD1fc1n5KtB2QIjnq06lgDmsuhnX5y0ZuC2CPEa9IshXmZjJ5LTTAUc/r1jPUfgCIbx/oB9PbmrHzk4LAGD6+CCQFEBRFKqUDnR6ddJ4arPfaSbJV6EE02RQvu58AujdBZz+45R208dMtpMicfQlQN9u4OXbiB+d2gB0bgJaPgICHsypLMT0Uj3eSzP52sP8H6oF/h8kX0uyoXxGYWqfQDCETw4Pwh8MwRsIYsDmhYJR4xLylSF0JoPtAFOcc3gkvu5LCdZ2AAC6twEA3u3VcwtwvVoOpy+IQQVR1bFqndICNae6bIh1LWWD59gQQnUBZl73e2hK6lGr9YWRr0Ss8IPzZuHZOyZaTt20ugFrZpZGfYsTm8h7dIWR9Ds6x7CoJorfaI7AqFXCyhZix/tC21jylelmiSEK8fhDoGlAq4pRAI7hNw0wgVsSEqAeD/nsP2uz44w/rcPm1hGoFLLo1xyKyu2xI0lUh3pxt/x1DMVLRbd2A29/B3j++qTfJxSise7wEN7Z14dgiBZdVJuyEGs7AACH30shNDY524F0gbcLEn9u7ewYg4wCvndu8l1CUxnLG8j4ta09tY5mln8SnB2QR9qRJ18zhI5RF1fRh9cOPHIWcPR98neqaj4AhYVGeKDKGPkqo/0ICCZfWaP9HJ74DB8FSmaktguHF/N++h7e3teHixdVQSkgZAjg/bj6w1JyUbmIqHHf+yFgH4jxyikOPzOpqVzI35eqSjxrnq9ClK/ClBk2TwAGbWJ/z/C2SYsrFY+pMOx+FvjvuUQxpDUlfLovicAtQdeJGWcDlBzY/Uzi52YRP3/zAL781A5OkQNA8gTgItjQ6y9A63Dq3lBZIV+D/qnj+br/VaBsHrDgyqR3sbvLguse2QIAqErGdkBXwt/++k5g1vn8314HKIrCvCpjhLIzHeizsOpdYf8Htvgi2TTBxixuDcKUr7948yBufWwbHlp3DD2M5cCtJzXgxlX1pI08K7YDAZGBW+TD06sJOen0SWw3IyUcA9x47u/YDABopyu430uBWgGHN4g+K/kuinXkGkFRFEfQxvTPZhWvYZ0ZMhkFQ1EpKI8FGOskdzLKV5NOJVp1VWnUQiGj0MW0dLp9QezrtmJZQ+4qAo1aJV+ItXTyD9A0T76yPu4x1iVuxmYhpp1IItsBCa1JfR7y2xh0U2gdcuK9/f0JSIYcHjuSRNO6r+L7yhfhHO6I/aSDb5BtCvPnrjEXXL4g100l9Lo+5cGKOZRClK/M5//eD4B/nZzc+yVpO5AuyFKoiR/otWFaaQHvH51HBOZUGqBTybG7y5LSfjpGXKgvFhAIl0fGkBtn7xRHIBhC96ibb5fq3wc4w6r+QsJ4EsBcqMEwbQCdIfJVFfIgIBc4+DKkUs5Oe0JBYLQVMDcl9fJ1hwcxaPdge/sYnL4gNEoZblwt3L6AncT028aRrwDxNQa92QABAABJREFUOp2EwUKSwOckC0+5krceEOSdGgfqwgwrXxnyVajnawLlq8cfhC8QEuSLFO5fJ4ny1esAXv8K0LUZGG0DNKaEL+E8XwUoXzn6QMiForACmPsFYOdT5LgCmfM7E4Pnt5IF7uEBO2QU8I0zmrjgGEkQCkLtG8MIDNjSKoHfd9bIV2HBjQByV73kcwJdW4CmM5KWcdI0jZ//j/dnTUpdpGeUehULAPN0YMEXw46RXPsiSJg0gSXNhFonsJ+YZEVaazfZClC+fnZkCE9t7kCRTol/f3qMU5qcPbcCv7p0PiFzONsBqzTHJwSCzw3m+sp8dmqFHCqFDHu7LYnbkbMFex8XSqfs340h2gBKY8AFjH+kXq3AoT4b7nlxD0w6JRrCyNH6Yh2Ucip2cUJjAk69F5h32bj7jaTrjP0OU8hIkMsoVJm0+OjQAG5/Yhs+PTKIQIjGiklDvrbzDwQ8/PnCKV+jd+S5fKRDK8J2IBxx1iBSK18DXkJ8e0HmQ75gKDbJQMlyd+xIAXKKzLGCw62RD7RvADo2kdss+ZpCl2Vzf6Tinw25O+7BdkII+WzDyW93kteeHLUdSGbcPthnw7wqiSyzpiDkMlJobE9BWEHTNDpHXajNk685BUnIV4qizqMo6jBFUS0URd0rxT6nEo4OOuALhjC3krnIsO0Gp/2IbIsaUn6PkgIVhmkDArYMka+0FwGZsMGX9XzNWeXrWDtpfU2CfA2GaNzy2DZc/s+N2NdjgVxGYfdPzyFtigJRwUxibn50Kx7+7Bi5s2oJ/wSPRfRxTQn4XHwrz8V/A+4bSn3CoWJsB6SUX8QDm2oqpMAioC2ODVBJ5PkKRLb7WqQgWg68yt+2dYtSvqqFkK9ijfuX304W0S/dDPy6jF885ggO99sRYv4zwRCNU2eW4p5zZkmbfO0aBQUaXlUxtrTFTpkWjKyQr76poXzt3ET+L9NOS+rlNE3j0Q3t2N1lwffOnYWP7jkVakUSihBW7WckIUGYcRbwxafIbYZ8NekICRMKpe+z7LV6UKRTCla1pBLcERW2HpLCXhA99BIAxpw+BIIh/OmDw6g2afHCl1eDBvCDV/ahUKPArPKwBTVreZNJ24FQIDJJPha4D48f1+QUhfcPDOCWx7am6eCSwLFPgH0vE1J5tBWo5Vv9O+gKrPvuaVxSvZ7xrfUFQnjpy6thDMtLuHp5Lb5yWhMUsToqKAo4/YccuctBY4okPeK0yAtBTZEWRwYc+OjQIL75/G4oZBSW1CW248kWwslXeixM+eqxEeWrxgSYyHXjgxYHDvROLDS4GTV11PNaoU2YOyHlJSfgJQUeH/jfRl0UH2AAgm2dJgWsPcCrdwLOYciYvI9VLX8B7q8EnruOFKMfvwB47DxSFGTzI8JFPyJxZBz5mle+MmDFHELI1/Fqck8qhbxcIV/JVuxpPer0oc/qyZOvCdBYokPHSPJdSiNOH1y+IN95nUdOIGXylaIoOYAHAZwPYC6AaymKmpvqfqcS9veQCyxr2g8bQxKs/irwoz6gPPWPq7RQjRHaiKAj+cFVDFQhr3DlK+P5mpNr5lAQ2PAAqYrXTvT8SgQbM5HtHnNjb7cVM8sLI0IbhKAsTAn3m3eayY2CUuC7R8nC0dZLFBpvf5f3QT0e4Hfy5CtFiUqqjgl28uOXoEVbCDjlq8DArQQniZ3x8BOifJ0RRhzYpCBf2bZEFgKUr94AWaiJ8XwV7F1at4qQhS0fkb9zzP/1UF9ke3JFMuFJicAsdIvLqlNuTQLAf6cZ9XwV2Fqd68rX9g2EKKtbndTLP24exK/eOohTZpTg9lMa0VSWZIsoGwgVHjTFXve8vPI1RAMOX/oCmfosblGetaLP/0QYawcM1TF93D3+IE79wyf49duHsKfbijtOacTM8kL847oTML1Uj0dvWR5B+EGpJd9vRm0HhAZuTSxMsO3hnSks3CTHU5cCr3yJEK+hAFFZMqR2n7wK5gJ+LsSGhqnksgnF7NNnl+Ges2eKf//xBUNXagWr2iJ+QesLhvCbyxZE/mZyDAatEjZmDuEeClNKHnyd/DNUA9oiuOZejX/3NODmRycS9+zvKqrytXgasPNJoG9v1PeXUZSkl++Azw0fLUcobCnbENM+YgoFbh1bC+x9AXjqMnJdAlDlPkw8vg+/Dbx+N//cnp0kEM08g5C2DywGDrwm+i2bB3jyVSWXoTifmE7AFuOEWDqM94Xt2Sn+/TjbgVwhX5OzC2ruJ+PonMo8+RoP9WY9OkddCASTKxyxxG2efM0tSKF8XQGghabpVpqmfQCeB/AFCfY7ZbC/xwq9So5GdlJg7SHtT+oCQCXNCWHWqzFCG0ClWMkXCjU8CMoFLqwoKjeVr45B4A9NJCRl1d1AqfjJfHjr5v4eKxZGTVmNj3B1U8QFsqAMMFQR0qvlI2Dbf0hb6/ECnxNQSjxgsC25GSpSiFK+CrAdEKN8vfyEaqz77mmQUYDFJQH5Op6Qk9jzlYVgZYxMDkw/g/873MMuB8AGDk0vJdf9Cqnb9MY6gM/+AIAELo46JfD1VWrIOZdx5WtyBFNOYWA/UDJLWPBGFLBk/cM3LktO8cpi/hVAUSOw6i7+PnZhGGY7AIAP30kDei0ewZYD4ZBMGTdyjNguxEDbsBM2TwBv7iFFJbY4fsbscqz9zmlc2AUHirEe8GaQfA0GkrIdCEdOLm57dpBtyUzggj9in2IBDhefHvEUPRPoVGnSSBcUomHnZxRQsTChSjMR2GCzu06djs+/fzq+uLw2xQNML4xaJQZsHjy7pRPu4bDx8t3vE7uAkB+gKAye8RfsoGdFHVNcvjierzVLyfbjX0d9f9LcI931m/Z7EJSp8dityzkyPr7yNUfHDgB45/vAW98W9lxWhNG/NzKY98Svk3Nq/8v8fc1vk+3sC8j3O9bGK2FFYG+3BSfUmQAQOxxJO3gmM7wOMr7KBMxxx1t59O4S/36c7UBuuEbydmHizi3WDieZOcLxhEazHoEQjV5LnEC9OOgcJUKjumLpgn7zSB1SnL3VALrC/u5m7osARVF3UhS1naKo7UNDmWmNzxXs77VhbpWBn0DaegSHQAjFjPICjMAAhXs47RMMmqahpn0IilC+UsjBec/BN0gL2gV/BM78WVK7CCdfx1x+bnIiFt85eybKCtXos3oiW0ELq4g3GksssSEixwPCbQekgpFZHGWKqBOlfBVjO5CYrFLIZWgo0cMglb+jazSSDGdb1OOAI18F2Q4k0b8041z+9li7iBemHz0WN4r1KsxkFMgVRgm9XgHgvXt5P2h9CRzegDRt5Nqi3AzcynXl6+ChiW3OItA56kJpoTr18AlTHfDN3USFxoIlXxmVDke+ptH3tdfqFhUYltT5Hws0ndDHvWWQENEjDMEkKHBJbciw7YBA5WsU24EN956BxbUmOLzpUzcnjUNvkW3JTLjnXIkrPT+Gu/GciKewoWGSKuzYIuj004nKM0Xla1kh2d+y+iLUFOW+sujKpTWYW2nAj17bB9doLxz0uPNzwVUAeHVrtOEkqu3A6q8BNSuIPVTNipi++sTzVTrQAQ8CMjVOn1WGk5pKUKRTxmljznHla+9OoHe3sOeGW2c4wgJ5G08DrnoCuPDP5B8A7HmOqF5LwhLlx3cxJTo0ixtdo25cuKASSjmVnBf5VEEoCHz0c5I3QNOkGCfUSzfcdkCpS/L6k1u/4WSH7WEHGXdLCvIK6nhgBVltI+K7Nf+5rgXffmEPKAqoLc6T3LmEjJVOaJp+mKbpZTRNLystLc3U22YdwRCNg7023nIAIN6EAkIgxKDcoEFQa4ac9qddmeEP0tDCi5BCqPKVeL7m1pAB4MDrZEKy4o6kW9rZFi4WFy2qSmo/Xz9zBr5+5gz4AiEMhgdkGCrJRMnK1DesxxP56pSefDUx5Ku1K/7zpEKQ+S4Feb4mth1gf29ClK8sTFqlNJ6v7rFIJZnEgVtcaqqYK8WCK4Gb3iAkS46Rr70WQj6xwWeS2w6EtbkpCktBS9VGri0C3JbU9yMUQf/kV756rOSaItJCqGPEiYZ738bm1hF0jbpRl65QBHV05askivgocHgDsHsCIm0HyFaSmYJzmMyDimMrX1nyFQD0KrmwRaDGkFnbgRTOjWqTFvVmXW6Sr4ffJgIEdQHeP9APbyCEc+ZGevOytgNmKclXxh8Ty28HdGbAmRr5etvJjXj81uU4c06ZBAeXfsyvNuLJ21aiUKOAwj2MNrqCe+xX/uthXf5teANBTt0KkALqQ+uO4aODhOTjbAfCyddz7wdu/5AwMVoTaX+PAoqSLlCPpmkg4EWImVstrS/Crp+eg7LCGMRgritffU4SfCYEUYLiPLQSdO0KMgYt/xLvPe6xAPUnkk46FiLI10GbB89s6QAArJpmxszywuQtcaYChg4D6/8C/O9rpPjtcwizHAAii8xKXczzJC5yzHZAlqTtwIjDC4WMEmShdjyjsYSsgVuHxAdF//69wwDId5NSN1UekkMK8rUHQHivTQ1zXx4gaXWf/+B03HVq2CLA2h3pxyYRikoJoUunuaXaFwxBS/kQUohQtYCWtN0oZXisQMcGkpieAsKVQxcurOQWDMmATWntHA0bkA1VZPI0fJT8zfoFHw/wp8F2wFBNSE5LhsjXANO2p5DKdoDxfNUKn7BIlmzuHiW2DaziVYztgBDlK7MVJd6Uyckio6gx58jXnjE3qk1aLmVUctsBml8gqwrNAHhldErItPI1JJBgymXlK+s3XDZP1Mt2dpLP+anNHegcdaWPfOVsB4h6wqQji8B0KV/7GMsNMaEsSZ3/sTDSQrZxbAdawhYz9Wa9sDZatSGztgMp+iEXqBVw5hL5Gv5/qZgPAHhlZzdqirQTbB4CzA9BUuXrvMuBu7cAsy8E9GaiPEvheqKUy3DarLJJ1YJt1Cnxi4vnoJSywmfk1fEDdDEu/sd6/H1tC6duBYAPDvbjd+814/Ynt+OzI0O87YAyxlxXqQX87qgPURJ6vrp8QShpH2hBlk5AzitffY6Yn9sEuEcBPU+mNtdfh4t896PNHjbPYoLTAAALv8hbbgGAnSFf+/Ym/P3/4JW9ePATEgQ8p9KAp7+0EvddmHyHx6RHeGhZ6yekE0Ko8jX8OqHSc+OxOLDka27ZDogtqow4fCjWq6SzlJmiKC1Uo96s4+yRhIJdewGEh8ojtyDF2bsNwAyKohopilIBuAbA/yTY75RBSYEa5ezC2+ciA6dBWuUrAJTXNAAABjqPSL7vcPgCIWjgBa0QtlCkGc/XnJr2WDoB0EC5uMXyeLCL15fvWo0Hrl6c0r7YhXdHeHtBIaOk7WKCD44r5atLMk9kDnIl+UwzrnwVGLgl2HZAOMlv1KlgdUngB+oeA7TFgI5RDwkK3BLu+UqlErhT1EDI1xwg5qwuP65/ZDOODjpQZdLikkVV+MlFczGzXGK1iGuU/L9vfgsFWjK+2D0SkGlaU1RlTVrAqJcEnR+5rHwdPEi2Im0H5IxP3LDdiz6rG7VFaWoNYxeH3nGer2kiX1m/YzHK15TO//EYJWRBPPL12KCDKwo1lAgcZ9QZVr6GAjEDwyLALcQnkq85o3wN+kmhhcHAoruxp8uCz48O44vLaicswtnjLi2U0K5FJgPKZpPbuhIyPmfSRiJHcPmcAigQxKy5J3D39dNF6Bx14VCfDa6wDooXt3dDJZdBKafwcfMgRp1kTmPQxiJfYyv6KEinfB1z+aCGX2BhG4LmV1lFPOWr10ECd9kCs2uUkKtMUa20ejpa6Bpsag1TcocXNOvGK1/7iO/yv08hwV1xsLPTAgD41lkzIJdRKNKroFMlLzKZ9GDFTSUzScim1xFpJ5AIS24GLvl78uQrJ9DIDUItedsBL0oKJLbimoKgKAq3nNiAnZ0W7OoULopgvV5vWFWH/33tpHQdXh5JImXylabpAICvAXgfwCEAL9I0fSDV/U5ZjLWRbVGD5Ls2TVuBIE3B17ZJ8n2HwxsIQgsfaKXQhRVDvubSvIclMVNQIO/psuDYILnAzasyQiEiVCgaqkxayGUUXtrRjREHQ9oZKsmWXbSI9Gqa1PA5hbfziIGpNoOeryKUr1Rs5WuPxY2uURdsngAoCigQMfk1apVoHXJid5dF8GuiwjVKVJFs66bEgVuyJCdxAMj11GvLrGIzCra0jmBt8wA2tJBFULVJC5NOhS+d3Ci9Oso1QmxTGk/hWrds7kmmfA14AdBcYnNc5LLydaydqPqMtQmfGg4LUxQ52GdDiAankpYcciWxPhltBfr3wcQkslvcEhRloqDPSkgEMcpX9vyXRPk62grIFICxLurDbl8QrUNOnNJErmWCwyi0piz4IYuwHRh3bujVCngDIfiTTEqWFAxpPaaswD8Dl+Cad2nc/84hmPUq3HZy44SnX7u8DlcsqcGda2IT6CmhkJlbhXtmHi9gCCRNxQzurgGQjpbuMTdnLQAAnx0ZwhmziafqZ0eGsK/Hxo1rURFH+SqlAMvi8kMDHwmJFII486ucgM8ZW/n69j0kcHfvi+Rv9yigKwYKiW1EcUkZKgwabDw2zkbjuheBm98kRYdw5WvIz+9rz/Oksy4UxHiMOX2wuv344fmz8a2zxAcST0mw5Ou8y8l6fqiZFOWE4pK/AUtuSoF8zS3bAQrJFU2HnT6Y836vgnDl0hpQFPDpEeF5Sayt0tXL6jCvSnwQeB7phSS6dZqm36FpeiZN09Npmr5fin1OWfTsJNvKxZLv2lBkxgG6Abq+LZLvOxw+rxdKKgiI8nwFckqxxLbvJ6lA/suHR/CFBzfg0Q1tUMll0ChTP5VUChl+dMEcbG8fxaMbGJI+vI1Vrjq+ArfSYTsAEIIkU7YDQS8AihABCRF7MvX1Z3fi1se3web2o0CtENWqI6MAuzeAKx7aiKMDSap8QkFi1aErJl55gGDPV6WcEna8zGQyKWVMCbMwGDos/rUSoc/qxtUPb8bP/sfXHotiLVClgHuMfB/gldDSKF8Z8jUTJCerkBJ0nuew8tXeT8gcIYnHYRhzku+LVbSnjXwFiDpnz7PAE5dAo5BBpZCl1XZARoHv+BECVvkqxfdr6SJjuzz6dXdT6zB8wRBuWFWPc+eV4+xxfqMxUVgJOPqjEhVpgQS2AwCybj3Qb/XgQBspeP7SeRme1N2CtmEntraN4jvnzIpq12TUKfGnLy7iVNqSgyGuYO9Lz/5zGQzhrDDx899BmpCvPRZ3hO0AAJw6qxRrZpSiddiJN/f0YlFtnMW8UhfXdkAq5avF5Yea8kMmlHzNZduBYICoXqMpXx2DvDp1+Ajwr1OAvj2kC4kpIFDaYqyebsaW1pFIEmzmuUDjGnJbrgSufZ4EDAOEdAVI6/w/lgF/Xzqh4+VQHymYzKkUQS5OdTgGyFpsxtnkb48lOZFIsp6vuWY7kGRNfCSvfBWMQo0StUW6CJ/6aLB5/Nxzjg0RYn9aqcS5KXlIgtw4e48n9O4kVbLwJGKJYNIpsTU0G6bRPXzKehoQ8IpZMAMABRlC0ihapIK1hxBi4a04ArG/x4q/fXyU+9ugVUqmavvSyY2oN+vRPsJ8xgWlwOyLyO3yeUTdl8m2x2wiHbYDAGnXsvWQCW+6EfAS1auQ30eMtjiHN4A93Va0DDqw6diIaIP6BibFW6uU47fvNot6LWgaGDlGiFfQSSlfhahegTDqOZnrBNvuzbZ/ZwEHe8l5afcEMK1Ej2+cOQPnzq9I8KoU4BolCzCEk68SKV+DXuH+c6mAXWxOduWrvZ8nc0RgLMwORKuUY1GNScKDGgd2gegeBex9MGmV+Penrfjj+9IXLHqtHpQVaqAU0Q0ik5Jbt3bHVCG3DDrwr3Wt0KnkOLHJjH/fuAxL64uE7ddYTQjRNPvqcwj6YxLIkYj+4bGkZratB655eBPufWY9AKC2qgLrf3A6msoKsLKxGNcsF6cWlwys8tXen533zyacjIKqgC86eEEKhQ5vAL2Mcv0nF83F769ciMtOqMYFCyq55y6Md51SagmpFOU6LZMw84q1HZCrhIpAqJzlXuFnFJABz8QPqH8vf/vQW/zf2iL+N6wtworGYgw7fPzaIRpmnQ9ULyG3PRZg5nkkrHTeZUTFOXIs4un7eqwA8uRrBJxD5LwJ714V6vkaDlXBFLEdSDZwyydtmOIUx4yygoTk6zee24Wz/vwp2oed+PDgAKqMGuhTyKHJI33Ik6+ZRu8uoGqxaIWMEJi0KuwONUER8vIBTWmA38MMGCImPRRyZM0cCgFPXwls/iejVBKfAPiXD4/ApFXikkXEjzWm91WSqC3WoSs8dOvSh4BT7wVW3En+ZsNdpjKCAUIApcN2wNxEwopYC5B0Iugj7b5CQCFqW9z29lEEmcrF4QG7KL9XAPjKadPx+fdPxxeX1WJDyzBCYqogRz8A/r4E2PZf8re2GCibS1RlAoovvkAIaqWwc4xLTRV+dDyMNYCqkLSAZQj/29OLd/bxqilWJQIAq6abcc/ZM1MK4IuLgJcs2HSENGID2GxSKV+BzLRXswSvKOVrDiJJ8tUSRr4urjVFJohLjfAF4lAzBu2kQPvf9W2SKyP7rG5UmsQFzLHti5IUaeOEmt7y2FZsbR/FidNLxCcAs50ymepACflTUr7qOeVrhpS6MdA+4oKBYpQ4tdVQyGV446sn4ZnbV2YvcKWQIR6PY+VrRCt6GFoGSYfM9Svr8MVltdAo5agwariU+4XV8ZSvWjKPCU60NKEgpfKVkK8K1RRQvoaTcOPVr/37ybZiIRAIK4iG2Q5AW8QVkHZ0JBi3TfX87VN/AHx9B7D66+RvF29b8Mjnrfjtu82oMmqk9V2e7HAMENGOzsx3f4rxfGWh0k0R2wECMR0rLl8Abn8Q5rzyVTCaygrQ3G/HrY9tRetQdBKWtZb7woMbcLDPhjvXSC/yy0Ma5MnXTCLgJQNp1ZK07F6lkMGlYCZFaUzkZZWvlGBVIhu4lQMTn+5tQMuHZIIj0nLg9V09ePCTFnzeMowrl9ZgYQ3zWUv836or1qIznHzVGIDTf0gSehUa4MOfAOt+F7/1cbgFcAj3h8k5sEqAdNgOlM4i20yQ2AEvoBBa3Y2+ONjcOgqlnMJZcwS2xo6DRilHbbEOTWUF8AZC6LfFCHWIhtFWsv30d2SrLQKW3wF8Y5egyZ8o5Svn+ZjECUVRRP3KfqdvfA34dRpVpyBV5ruf2Ymr/70JL27vwsE+GwrVCsgoYMW45G7JwbYHjlO+bmkdxfb2FMOyMkq+Mtc5hYAFtETKV0kCnazdwDNf5D24WdsBkRh1+bnfzPfOm5X6ccVDeKjZIF+kcPuD+PCgtL6XvRYPqoziwsP44I4Uv59QkKR5GyeO7zRNo3vMjWK9Cj+6YLb4fbNzBmt3ascoBDTN2A4IKOBwH15k8a5Awypf02MvIRQapQwGkHN9Zh35DPVqRco++SlBXUgKdrbjkXwdJKQ+e60fh6MDDsgoQK2I/H4eu2U5bl5dj6UNcZTi7JwtSks1Jany1Q81fFCoBc4RpXxzqRFOwo3vOBnYDxhqgPL5kfdri3h1v74ETaUFKNQosKMjwfivLwG+sgn4QQevgtWxYz7/2g8ODGBGWQGeu3NVEv+hKQzHEKAvI7+nAqZ4kZTyNUnPV258zA3yldWRiTm1RhykMJP3fBUOtvD1yeEhvL6bz35pH3biF28eQDBEo56xrbK6/fjeObNwy0kTvdTzyA3kyddMYvgoUTJULEjbW1Aapj0kja3pQS8ZMIS3+8iAXAncan6Tvy2yWvmtF3bjD+8fhi8QwolNJWgsIe3cI05pQ0vqinWwuPwT/fg0RqDpLKBrC7DuN0Dbp9F3QNPAP5YC/zld0uPKKHzMxD0dtgMs+ZoJf1BRytfotgO7u8Ywr8qIb51FwjGa+5PzbW0wk8+yfVjEhI9tT2QD33TFZLYlMGHYGwhyieKJwFXQk71OlM0BBg6QHex6KlIlIjHYc1OtkGHU6cP3X96Ld/b1Y+W0Yqz77umcKj5tYBdJjOerWiGHSiHD2/v6cOW/NmEslWtSzitfY/9AdnWOYZgNK4yCDS3DWPiLD/hAw2Rx5D3g6PvAK3eQBZTXmrTydUl9EVp/eyGW1AlsfU8WHit/e+gQXr5rNZ69fSXKDWp83CxdGz1N0xiwecT5vSIscC/VeYJjgJCWUZSv7Hn7tdObMK00CbUSu89MKF/Z4qqYwK0JtgNE2evIovLV4Q3A4w+hkCJjelNdcj77aUFhxfGpfHUOEfUeRQHfb8PQV8lciC3iHR10QKdSTLDTqi3W4RdfmB9fMc5ayESxrZGWfPVBQwUgFxH8m7vK1zAlWzTla/m8icUkjQlYfC1w3UtAQRlkMgpL6ooSK18BoHxupG0U6+PPFHV9gRD2dFuwZmYp6s15z8gIsMpXgJ8rqZK0HUjG85UtsOWK5yvXsSL83Bpi5l8lefJVMKaX8fOVTceGuduv7urBYxva0T7ixDBDaheqFbh6RZbsfPIQhNw4e48XsC2xrD9hGiDXMuSrN8lgHQEIMspXmVBijAJkuaB7pWnimVTALJKTVDwoZBSWNxSjgSFfpQ4tqWOqVxHWAyzWfBdoOIXc3v0sWfhveRjY8ACZONn7eU8oa4ZCpdIBtiKcDtsBlZ74vg7lmPI1ShovTdNo7rdjTqUB86uNuHPNNPz+yoVJHQr7e20bEUG+jld4sZN0gfAFQ4LJ15RsBwCyQHGPRnr4+UWofEWAbfv5x3VL8MG31+AH5xEV3ayKQtSZdelvpR2nfAXIhIvFvz49Nv4VwpEV8jV1z1eapnHZPzfi9D+si7mLfT1W2D0B7O2xxnyOIDiZyW/HeqBzE7mdhPJ1zOVDkS5NgULjwbaUKjTAYDOWNRTjxKYS1BqVsDqlK1Q4vAG4fEGUG8S1FCaziIsK9poVxfN1iLFaSLqNVltEWk1tvYmfmyrYgpco5Wss24Hseb52MOPNaXVkHFTp01xkEIPCiuPT89UxwFsO6IpRVEzIpKayAugY65OkLVA45evEa4qMoiRZCby1txfHhpzQUH7BheBJqXwNeEnIVsX8iZ16AQ9RXM48h7trWqkefZYk5jxqA7nOMGPEwT4bvIEQlgn1wj5eEAoCrmGefGVDZ5NRvioZ2wGxv8lcsx3gOlaEY9BGxuGyQnEF2uMZ86oMuHhRFc6aU4ZdnRZuTGezJnrG3Bi0e3Dtilq88bWTRGeD5JFZ5J14M4mhZoCSE8/JNEGhMwJWpNV2IMSoEuUqoRVR1vM1yxOfwYPE5/PCPwGdm4Flt4l6uV4lh9MXxIrGYhSoFVAVkUmmVqCnpVDUhpGv88d7a1WdANzyFvDWPcDuZ0jr2J5nyWNHPiBEAJ1dfzdJkE7bAQAonZMh5atXnPJ13BRm0O6FxeXHrHJCQv/oguQLNxUGDdQKGTriBTKwcA4DT1xMgunqTgSufBTo2Q4Ui2tjEWM7wIq3RHnShqNyEdl2bebv81gBwWnIwtEaliRKURS+ctp0LK0vwuzKJCbhyWCc8hUALGFFoG2pWA/kKvnKIfrvw8kkdNu9Abh8AehUE6c3A4zlRnOfHafPih62uKFlGHq1AotrTbEPYawDABCCDPSnf4QcEKR8DQRDWPKrD/GTi+biqmW1sDj9KMpU6ITHQrbTTgfaPyf+5zIZfm27D21UNYATJXkb1ku2TCT5ivjcunCwRccoyteUyVeKIgq0TNgOiFGFcyqoGIFbUgTxJYn2YTLeLK+QA31UegqqyaKwknQShWPoCNlufxQwVAEnfSPzx5VuOAYjrlcKuQxFOiUqDBqMOHzoHHUlP6/llK/RbQdS9XQetHvwtWd3AQDUWr8wyxr2zaN46ucEYnm+jraR+XzJLH6sP/nbhJSdf8WE3Ri1Sti9AQSCIXGWHhRFxn1mXrGjfQQq+LEkT75Gon8v+Q2xYws7VxJSIBsPlR4ATa7zSXX45Qr5Kj5wa9BOfuOi5wjHMdQKOf5+7QnY0DKMjw4N4ivP7MTvr1jIZU0c6LXBH6Qxs7wwua6ePDKKPPmaSQw1A8XThFdqk4BKbyI3MkG+ivBaorKvewUOvQmAAuZcAiy/XdRLnd4AnL4gvnLadNx16nQAxGP3D1cuxIIaY4JXiwOrfI2bbDj7QmD7f4G9zwOzLyIqnx2PRRKvpjpJjyuj4JSvaSJfS2YArevIjCGdFeSAT5zn67jFAWsxMKsi9bRZmYxCvVmHNiG2Az07SbECIBNNQyVguFj0e3oDwpWvKX8LFQsICbH/Ff4+j4UEq/g9xPNSoqDD1mEHFDKKO1cBYEVjmn1ew8GqGMOUr2woW22xNoKIFY1seL5KoHwdtvNWAh8dGoxq/cAqLg73xx4f73t9P8oK1Xjhy6u5+9y+IDRKGd+Ga+nEUNES7B8O4vQu4crXIwMO2DwB/N+7zZhfbYTdG0CRLkPka0E5UbzNOg848i4wegwwN6HBdxRm9Eh2LWQ/43KRqhaZVNdhlhiN4uk+mCr5yu43E+SrqDEwhucrS75mUPm6r9uKbzy/C0/fvhKbjo3guy/twWrZAZTu+ht5QhrCZpOGoZKomMMD8x5cHvmcqUi+OoeAysgOmm+cOQNNZQX460dH0Tnq4hSwohHHdkBGUSmLMMLnxSraJ2I9NUlsB/we4JPfMPZ0zHld0gToSoh4p/FUYHp0SzETF7wZQLHYop7ODBx5H3jqclQ6mvC55iWUF4if801pfP4nYv827zLyN2vdwBY2xYAVL/mc4tY5nPI1N66jvF2Y8HNr0OaFjALM+jz5KhYnTjfjvgvn4M8fHsGaP3wCX4CM+bs6yXy9QqTdUx7ZQW6cvccLhg7zfpNpQoG+AAHI0mo7QDOqRLlamPKVhowEbmV73nP4HaB2Jd8yIgKsYmZ6aQGMWl7Of9WyWsyWgBgLR6FGiRllBdjRGYf8qD+RKCrpEDDtNPK7Gu8VFQwAr98NvP3dtP4eJAdNA+0byO10qWT0pUSVmoznkhiIUr5ObItjSaLZFdIoKuvNenQKUb6OhrWtx0gNFwKfGPI1iQp6BFR6ohA5FObr7LYA6/8K3F8OvHE3f//LXwIOv5vkGxHla12xDspsBcZYu4naomBiCNuKBjMsrhTIV6WOENWZIF/Za5Yg8pVNdoiuXgr3et3cOhLx2KE+G+dFCsT2TfYHQ+gadaF12IlRpw8efxBjTh/m/PQ9/OfzVu55wbF2jCor8HDwIub4dZwnH03TMdXbe7otAEjh7vwHPgeAiPEkrbjtfeCa54DqpeTv/a8CPTuhod0opUcQGuuU5G2SVbWwi7iUbQecQ0QNp5k4LqesfAWAogZgrD351wsFV5gQonzNHduB13b1oG3YiX9+0oJPDhMv4Z+Vkd86zDMydhyCsPh64qn74s2ELAxG+Zymmi1BKESUr/rIefCtJzXilBmlnA9j6rYD0ecZqShfH/ykBS9sI8p2CiGoIFb5mu1FSAyEK1/7dpGA07W/BEaOkvvMM4CieuC7R2MSrwBgYgp5FlcSnu/aYuJ/fGwtVg29jHKMTrzODR3muj6OO3hsxLZu6a2EgAWAVV8FCquIGEYsOPI1jsgmGjjP11xRvpKtKNsBuwclBWrI023PNQVBURRuP2UaXv/qSRzxCgA7Oy0AgHJjnnydDMiTr5lCwAuMHANKk0jYFQGTTg07rQOdxsAt+EhFW6ERaDtAUWTek82qcygIDBwE6laKetlzWztx43+3cAbhZaks2kRgeWMxdrSPcWq2CVBqCQELEPK1JGxRwxIyrhFiTbDtP8DWh9N6vJKi9RPgk1+T2/qS9LxHptR9ARHKjCi2A1taR1FuUEvWmmzWqzAmZGI+Eka+ivR5DYcvGJqQmBwLXOBOKteJqsWRf7uGgfV/JrdZJa97DNj/ciRJKwLDDi82tAxjbpW0RRdRGDlGlO1yvnllVjkh6CuNGlhcvuTtG7gWxEwqX5ML3AonOllizaBRcD5YALC7y4LzH/gcG4+NYIAhBo8NObiJa+uQAxtbiIdrz5gbgRCNIbsX5/71M/z67YPYwIQbrD1EiKTNR/sBaw/2uUzYFJqHh0/ZCHz7AOf7dt/r+3Hh39dHVYLs6bIAQMQ5OK00Q4EmxY3A7Av4Oci63wCPnME9/Pv/PI6vP7cr5bfhCU5xi4AEwmbhcI1FKMLDMeTwQq2QRfgji4a5iVxX0n1+cMpXIb+P6IFbbHHo7X196LOmL4AwHHYPKfy8tbcP29pGcf78CsxWjxHLpJveyMgxCEbpLOALDxLrgVdu58mucLR9nvnjSifcY6RDKoYIoaSAzFdSVr76JpKvxPNVPH755kH8fe1R/OH9w3iDSfpWgSHKp4TyNYx83fh3sh0+Qrp4Csr5QpI+/lzMyPiHJ9X5EmZhVBxiipcD+yOf89qXgQ9+LH7fUwGjrQBovngJAKUzge8cIvYkYpGgSBEbufUbliUhmhiweUUHcuYRiZnlhXjsluWYW2nAtFI9Jz7If66TA3nyNVMYaiYTnor5aX0bk04JB62F35VioEgc0MxgoRSofCWer6HsFp2t3STAoni6qJc9t7UTnx8dxmFGKZWSYkYEljcUwe4NoDlOeyyW3w7Mu5wsBsN9hG97DzjtR0R1ycIijaopI2hdR7xsv/wZselIBzJFvga9REUoCJG2A1taR7C2eRDXrpDOPqJQo4BdiP9fuPI1CaU4CzGeryz5kpIn3IIrifdr09nk7yPvEd9XuQrwMgqD0TayDSeYBaJ1yIGvPL0Dbn8Q3zprZgoHmiJGWydcy1776onY89NzYNIpEaIh7HuOhYyRrwwhJES9xPxAntnSgS/8Yz0CwRDufmYnbvjvFoRCNDf5XDOzFLu7LFj6qw/x9t4+HGGu3Xu7rRi0eTGtRA9/kObUsT9+bT++9MR2ePxBtIeF0Q3Zvfjw4ADWHR4CADQygXVvfb4NcorGdgshW7sdNKArhj8YwqdHhvDc1k4c6rNha9sod7zv7uvDtQ9vxvOMasvjJ+f5a3efiFNmlCb98SUFeXSlbY19D97c08upFQEAjiHRbOiAzQO1QgaDRhzBmXLgHgv3aASREI4huxdlBvWEFHdRYMfakdb4z0sVopSvrCp84qenV8nR3G/HOX/+jGtNTCdaGVsbq9uPQbsX86sKyXhSd+LExPZcwPzLgTXfA5rfAprfnvh4x4bMH1M64WTO7xjjOjvHVSRrDxGHVCLiU/Fn+KMb2vCnD49E3KcGU8CaasrXsXYSqitXAf37RKnFWdsBazKdL9GumQMHI/92DPFhk8cbxph5o8jcg5hgu/rCv3shyFHbATEdK4N2b8aETFMZp88uwzvfPAVzmO5bhYzKf66TBLlx9h4P6N9HthXJJZULhUmnggNaBNJIvrILZqVWhPIVWZ73cAOncDJv0O7B3m7yOW5glFGZurAtrSMTIfb9o2LORcBVj5FJZUE5oCokrcjGOr4thoVjMPo+chEdG0l1mQ1QSgc48tWSvvcAiPJVKPk6bnHw0o5umHRKfHmNuIJBPBSolXD7g/AHEwRPjLYSYv+m/wHzr0z6/UTZDoCtoKdwoWg6i5D2lz5E/t7zPPn8513O+3Kx14LRMPKEpsnCOxQ7rI6madz9zE4099tx/2UL0FSWJVN7mmbI18hrmU6lgFGn5DxELe4kWg9ZZJp8FRS4RX4fH+zvw55uKx7b0I73D/Rj47ERPL2lA0MOHygKOLmJqOVHnD48sbGdI1S3tY/CGwjhymU10KvkeIdRA25uG4HbH8T6o8MTwugGbF68vIP4e9o9AQyMjOGK9p8DAPYFSVGkl0mXfuCjo7j50a3QqxQoUCvw4nbyuh+/th9feWYnNjFkb3inXdaCEa57iSzwGewNNWK57DBkCOGTQwPkzqMfAX9sIj6AIjBoJ6oWsQQnX3xJcaLgGuWu739fS74TFkN2L0oLUhzDOfK1JbX9JIIvGduBidf1x29bgX/fuBRufxAfHByQ8ACj49iQA/fOG8PTyvuhhg9Lij2EiDNLN45JjhNuINuPfzXxsYEDmT2WdMPB/Ab08ZWvbn+Swa0JPV+T2+14qMEQjFNN+QoA5fOBk75FbosIDDUlOfbTNB19ntq7k7Tbs/BYIv8+nsDOF4ukIl+Z67po8jVHbQdEnFpDdg/K8gpNyRAIkd/EVctqs2eFloco5L+lTKFvL6DUS3fhjoF6sw52aOF2WNL3JsykSiXYdoDxfE3fESUGO3CKIF/ZNlMAWN8yDIWMylg4SqWJDEysR2FCUBQx5S9qJK3I4eSr2jB5fMt8TqB3F9BwUnrfhzXKT7vtgFt4kjsli5jBtA87Mau8MHnvtSgo1AhIvw74iFLaPB2YdmpKASm+oBjPV7KV5DrBfr9BHyHyjTXkuw6FeB8z5yC/kNjzPPD8dcCOx2PucnvHGJr77fjRBXPwxWW1UhxlcnAOEZ+wGGSGiWk9HEvF91VblP7CBEDGEpkyphozHNs7yPEM2T1QyWW4/51DCNHEZuGVHd0YdnhRrFNFBCBubR/F50dJ4eyzI0TBWlesw1lzy/Harh5c+/Bm0DSgUcrw4cEBtA07oVPJIZdR3LnCwuL2YcO693CCrAW/DN6CAzQZy9l27rXNg1hUY8R7316DixdV4p19fbB5Ir+DV+8+EfecTRTTepVctDpUMsw8BzjvtwCAoFyDD4LLMEvWjf3qL2F+51PAYDPfXiqSZBy0paZqSZmcCVO+ft4yjM+PDsHDEEm9VjfKRNohTEBRA7lWp5t89ScRuBXl6rm8oRjnzquAXq2AK83er6NOHywuP+5o/SZOlh/AmbKdWLbzh+TB8O6cXENRPVC9bOL9pnpg8FDuKiaTgYNcBxPZDrh8Sf5WOOXrRPKVgvjiSrh9jkZJLEPuv2w+fnIeM5dPcn6VUxhPwOnNwKk/IJ6ia74neDes8lWM5/uGlmE0/vAddHeT7ji7khQvPeVLgKMfAP8+hcybggEy70hjmHNOY7SViFzUEhVMwwO3RIH9DecK+cp2rAg7t/zBEEacvrxCU0JcsqgachmFb5+VY57qecREnnzNFPr3EcuBNCe9nlBrglumh9uePlJJFnDDT8uhUgmvOJPArSxNfDxW8vkrNIISqQGge8yF373XjDmVBhiYVu2SAjVkGTIIV8plKNIpI0JkEuK0HwJn/oTcDidfKxZEV77SNFEJ5RL69wGhAAlGSycyZTvgtXNekIkRqczoGHWh3iwiBVUAWEIpbkt63x5SXS9JPRxQnO2ABMpXFnIlKXYBxA9ZW0T+Tz47bzsA8CrYnh3MAfPhB6EQHUGePbulE4UaBb6wOAl/LynB2iXEsFBh1S+CvH1jIZPKVwHKPoc3gOe4oBXgidtWQK2QYW6lARcuqMShfjsGrCTEYUZZIaaV6DmSc18P6R4IMIv4coMGXzltOs6aW456sx5fP6MJZ84ux/qWYbSPONFg1mN+tREXL6rCPWfPxH9vXoYzZ5dhxOHDwWaigmszruaOrdfixqDdg0N9Npw7vwLVJi2uWlYLtz+Ipzbx4SQquQzzqgwcuVFhFK8OlRQlswCZEl59FbaFiA+sjvLirLEXgIdWE6skgBSQ4uHVO4E/zeH+HLR7RIdtAbztQNLlF9cosPU/jPKVkK9tw06EaBKQ5/YF0T7sxMxUwwsVKkLK5aTyNfZTCtQKOH1JqhkFonXIASUCkNNkfHmg5HUoO9eTB3NZ+QoAX/gH8X8997f8ffUnkjHD2pW945IaCW0HyPjh9KaqfI1mOyBe+eoMI4FnlBVi3y/OxfUr63HJPMb/VLCnPhVVGZ4T8Dkj7RN0JUREcd5vgLpVgndjSIJ8Za1wPhyrAAB8zfkl/Fz+dcjP+DEpjI61A93byDoKOI6Vr23S2qCxtgNiPV8524EcIV+ZrdDzetjhBU2LD+TMIzYuXFiJlvvPz6uJJxGyJLs4zhAKEuPyBVel/a0Uchn0hSaE7L0Ihei0kIWygBteqFAgdN8UBVk2la9PXkraZwrKBZPfT23qgNMbwL9uWMKlUp82K7PefCUFagzbRRAoM8/lb4eTr+Xzga6tZHQMH7D3vQy8ejtw13pC0GYTwQDw4U95TzhjTXrfLxfJV4oiCgMQ1cmQ3Yt6s7RhPIUaMjkfr8gDTQNPXEwIF9cIoNBG/p6ShFeU7QB/KNKA2ZF5RuT3PdYOqI2A10qIzMpFgK1nwquf3NSOn795EHec0og9XVbs77XiC4uroVNledgcOkS25ugLgSJdCr5vLDIZuBWjrfJwvx1ffXYn/n7tCdjSOgKbJwCogJ9dNAcrppux+6fnwBcMYd3hQfgCIWxuHcHiOhNUChk+/u5pAIgadU+XBUatElYmhGRWRSEMGiUevG4J914PftKCt/f1weULYM3MUvzuioWQy6iIwKK1zYM4V94LKAFZUQ0wbIVcRmHM5cc7e/sAAGsY/9YTak1oKivAo+t5on9+tQFqhZzzVKwyCVRspQsKFVC5EH6FGbsHeWKsmLaQwsUVjwAv3ZK4QLf3BbINhQCZDGMuP4qTCAhM2fP53e8D+14it3XFsHv8XPjX0UE7PIEgQjQwT4qgvKKG9Puos4tyIYFbnOdrbHJJp5LDmWbl67EhB5bLmrm/ld4w26TCLBetEqFsDvnX8hF/X/2JwJ7niPrVxHiv738FmHmewCC0HIRjgLSYa0xRHy4tINdjR7K/FUVs2wGKEq98DT+O+dVh526A6QoT6vma07YDDkK42ohVTbIhp3IZBYNGwY11QsB21z1OXYKnvQtwwemn4sbV9VAWaoDvtwL/Vws8eg6w6m7yAq+Nu9YfVxhtI+HGUoEtqoUV/AWBsx3Ijc+fEhm4NeYkv02zRCHCeRBktZCfh2jkxtk71dG/lwxYIiqYqcBsLoGWdmFnmsIVFH4HHBCzcCTK16zMe7x2QrwC/ORZALa0jWJRjQn1Zj1uObEBGqUMP7xgTuIXSojSQjWGxChfw8GSr0odMYgP+QmZ4h4DXroVsPUB3YwX3pH3pDngVDByFNj8ILDtv+TvgvL0vp9SRxYgrA9oOhAKkgW0GPKVmVh1jpKFd12xtMpXQyzlq2sEaP+ctLTTIWDGWXzCbgoQ4/kqWeAOC5a8MDeF2UxYyCS6kfG7ZO1IWDWpa4R7+fsHiDfefz5vw9b2Ubh8QVyyKAcIhKMfAcbamBY20ihfTaTtOZDk9UcoAp6YbaNb20bQMujADY9swf5eG1c4WNFIiHStSg6jVol5VeRa5/QFOVUpixUN5LkXLqzEl0+dhg33ngGDZqLFwaxyco6OufyYV2WARimP8M4yaclnWk0Nw68rQ6mJnBsnTieL5F+8dRCzKwoxt5LcT1EUVk0rxoiTfAcnN5XglpPI98WSr5XGHFApXP0MbGf9EV6ocIv/+3jlhMfhpZXwLbkVmH0BUFghPGDF2oVQiIbF5UvKnof3fBb9UoJwRZa2GO3DvKLoyIAdB3vJ4+x3lBK0RekdOwBxgVtxbAdY6DKifHVijryXv8NrJcXf77ZMHrJGU8TfrmMU7qzv69AR4OXbgAOvZf64pIJzhBB9MRbr5gJy7s5J9jyRyQgBG0XRl4wWhLVI+u45M/GD82bzD7Bjkyjlq/j3zwgGD5IOHRb6kqR3ZdKpYBEx9rMFqk6LDyPaBnznnFm8NYvGAMy5hNze/E/mFbR4wnCyw2MF7L3SqvfZ4o1X7GeZY7YDzFaovIr1ktZmW8SQRx5ZxCSZDU1ytH1Gto1rMvJ21eVlKIQb/9vTm/jJItFjccM6OgiXXMTEjJIxNecMzXzs/UDvbnK7exvZnvETouQRAJcvgP09VqxoJK2L3zt3Fvb9/FwYtYl9CaVESYFanO1AOFjyVV/KE5n2fmDLw8CBV4Ftj/BtL317Uz/YVMEu8EePAZScaxtNGygq/eo+L0lZT8Z2gA3+kd52gPyG7eOVrxamPfryR4DVXwPO+oUk7ycqcEuqwJ3xKAlTvjqHAXsfUTgVVhLS9bM/AMOH+cf79gAAxhxEEVJh0OCcueVoMOu4a0LW4PcArZ8QVXKMxbNRqwRFSeD5CqTf99Xvikku2ZhF94jTh/cP9PMtVeN+H40lvALt0hMi09SvWEoU9BctqMQPz5+D6hhq05nl/DnKkrnhMOmUWEy1oEHWD5jqUM4cyyWLqvCjC2aj0azHv29cGtFpMquCHyN/f+VCjrhnydcKY5aVrwBgqERBMbHi2a9dCXXjSpzp+yNaF32HPK4zE4Xnx7+OqmSLwMhR2Dx+hGi+ACAG7EeX9DyBLbAAgK4YbUzQmlohw/4eG/b3WGHUKlFTJMHnrjWlXxmelO1A7M+uQC3HqNOLCx74HFtaR2I+Lxl4/EH89p1D2NExhlnacW3JhZVAQWa7hlJC+O/IWEuK9syYwHVIsKFVkxGuEeIpGgN6tQKvfGU1/nHdCcm/h1Ibw/OVEj2+s+PA/Gpj5HVlqihfLV3A8BFgxtn8fbpUyFclLG5/hFduLIRCNOdZTtNAcbTr9qUPTQxdPd58X9nii5SB2epCksch1tIkx2wH2Jqa0NOa9V/XKqXLssgjj8mGfOkhE2j7DCidTVQkGYBKbwIoP97f04mfXjQXCgnT757Z3IHTgnZUVItQJlIAQCffTigWH/wEaH4L+O4RoHMzac9YcadgJd+OjjEEQjSWM0QLRVFQyjM/0BHbgRTJ14Iynnx1DPA+fiE/307asSH7bURhikMUlGXmWDSm9C6gWXUAS3InQlggRAdDHNQXS207EEP5OsaQr2VzgIXS2KPQNA1fMAS1UM9X7nWSvD2PogbiIwwQkpUOEkKgeBpw+J1IBdvuZ4DdzyDYeBres63D30/+AF85fzkoioI/GII8Q57PE2DtAZ78ArD6q4SwnBHbEoK0HiphTdXzFSDnR2EaVej+2IF0Q2HXPrsngHKDFrAA4xfQchmFb545A+YCFU6fFeljOLvCgGO/uSDh91ZTpIVWKYfbH4zall4ht+F19U8BAHTxFZxq1VygwlXLanHnmomKmNmMtyhF8YQrAJQXanDDqjqcPz8z84FEYK8JZYVqVJm06KZL0WXxY+3hFtyuLoK6bS3QtRkhpR6eYxugu/4pDI1Z0d6yH8tPPIvf0XALxkxEKchaX4gBV3xJ1pYxXKWtLUZbF7mGXryoCi/vIO28Z8wuk6Y9T2MihYnxVj5Swu8kCkIhY6EAv1ydSoGdHRa4/UHs67Fi5bTkWpujYUPLMP79Geki+EHJGKBvIApLnz2mt2jOgr32KTTEEqVmOdC5hdzHkq7OYaBjIwlzFKq8zBW4RhIWt5fWp1hkVOqikq+yJDKvWNuB8QGI8IskXykqNwO3Wj8h2+ln8PeloHz1B2msOzyEO5/ajkduXh7zeW5fEDc9ugUeP3/BLYrWCq4uACoXAvtf5u/z2ICJNcqpi/59ZFsxX7p9UhSZg7JdV4LBkq+5oZ1jO1aEFlVcvjz5mkceuXH2TmUE/UDHpoypXgGQahoAn8uKg33SVijHXD4Uy1zQGcUoGWTE8zVT856OjYSgOPA6Ub6WzxNMvO7vseLeV/bBpFNieUN2VW4lhSo4fcHkUmdVBWRw1pfypL+9H2hnwi9GW0mLOUAm4727pDnoZDGefM0Eck35GmY7sLPDgnKDGsYkSIx44MnX8cpXxr9QhDVHIviC5P8iXPmaYtvxeMy5mGzlSn5BPXCQbA3VZOLLEq93bYi4Rsvb1gEAVqo6oJDLIJdR0GRzsjh4iFhzNL9F/i6fG/fpRTqlRMrXNKv7/G7eI3AchuxeTCvRo4Rpg+WUolF+H98+eyZuWt0QdT9CCHOZjMLM8gJUm7RRVZtlFP85UIZqzKoohIwCGuJ4MrNq2pICdYSFgUxG4deXLki+rVdiKOQyFKgVKDOoUcMog1/e0YU/vH8YbS6e2JCt/Tl07R9i86ZPMfjMHVj+wRWwj/Twi8CRo5zVRdRFfEKIS02egPAxRFeMPd0WNJbocf9l8/GHKxfipxfNxR+vWpTcvsdDayJFnHS23/pcgEpM50P8QCG9Ss61fLokth840MvPMyupUcBQA+iY+ZN+EqleAb5wzW6rlxEvTlsfmUMBpGj32PnAn2YD/fuBN7/Jk4HhsPXyhc1cgWskaU9RwVDpieXEOCSjfGVtBwrU4+ZCnPJVePBvTipf971M/JBLwywVYvjxCsF8pnj40aFBuOOc54cH7NjWTsY1lgiLaRcz3q/ZM/G7ndLo30fOGYGBzYJhbhIf3Mhd43ND+coehtAzi7cdyNNPeRy/yP/60w25EvjaNuDEb2TuPZmqdillxY4OaRfPNncARsopanJAUQAFOjO2A5Yu3rR+z3NkYAuf1MTBm3t6cfE/1sMbCOLpL61EgTq7wvBSxr9QVOgWC5mMtC4ZqhjylQKOfsAn3Y60Ao5BsrCQKYGDrwG7nwX+vSY7i4UI8jXNfq8stEXpbavmyFeBJAslA0DD7vHj48ODOH++xBM9hNsOjCP0LR3k85DA55WFyyvO20ly24EvPgX8lLn+sderQaZ9zFDJJ9cq9UDZ3KgL0qbgEaJ6+vzP0hxTsmBJ4uEjZJtAuVRWqEG/LQoZIBSZJF/jKF9LC9VYUE1IkArOMiA948g958zCfReO8/V+69tA89swI6yIKZPjhLoi7PrJOZhWGlvVbtQqUWXUoGISJNA2lOgwq6IQJQVqVBo1nN9xOPnK4snPDkNrI0FiI+sf5xeDw0cxxnjcJuP5ytkOJPv1ho0hPpUJm1tHcHJTCdQKOa5aVovbTm5MKggsKjJhy+F3kWuTUCRQ9unD5jPOZAq6cXCglydjjP5BEpzJqvcmG/kqk5Mxmx0zahj1YM92Xvk61k627lHg6cuBHY8Dh/43cV+v3w28dHOaD1gkMkG+FtXzn1EYkrFddXhJEbFgvPKV83ydxMrXYx8DbZ8CJ34tUkGfQufXzy6Zh99dQQJ039zTi35r9HkAG7734pdXc90eMTsWDOPmoseb7UD/PhJKLHWXg7mJCB/EeOtzlq+5Qb7KRIomPD5x64I88piKyJOvmYCxGjDVZu79mNaIk/U92C4x+Wp1+1FIOyJ9sRKB9XzNxLyni2kPqz8Z6NkBWLtjBtMAxJPy72uPYkvrCL7/8l4srSvC2u+chvnV2e+pKWFaVZMO3br+RWDN94gKoWQGvziYcS7xVnUMkvunnQYceAPY+jDxNnvu2vj79buBF28GenZGf5ymxX/ZWVO+WtK3f458FWg7wCiXPjo0AF8ghIsXSU++qhQyqBUy2McnGVs6AVO9pO/VYyFth1UCg4Ukn0pSFL+IUWqIwpJVvhZW8eEJFfOZYgWzIJWr0VW0EkO0EcbR/STpd+0vUruAjRwD3vtR8j3V7GLH0kVaOhMo4mqLdegcmRh4IhhZJl9pmsaQw4sygwYLa0wAwpWv6RlITp1ZivMXhJ1zwQCw/VHg+etgDFkAALuKzgVWfRUABKnSbzmpAVcyvrO5jJfvOhHfPWcWZDIKVy/n5yqHbRPJypBrFKNB8l0UHXqGf8Dex6mtk7MdSFH5HhYMtndEBpcviFNmJN++GxcsMZfO0C2fU7zyNQ61FU6+soUxqXCg14Z5VQY0lWhQ4BsiRV/2ejrZbAcA8v2yc9zKhSScs3sbr3wNBxv01r0NOPoh8OJN5EccCgHd28mYE0pv0JlgBANEtZhu8tXcRMa8ceMdRVGiz2+2UDzBdkCs8jWssyhncOA18ltbfrtkuyxQK3DePDKOff+Vvbj18W1Rn2fnFMUKrlMhZnFqvOLTc5yRryPHgJJZ0u/X3ASAJiGwgpFrtgMEtMAT2533fM0jjzz5OiVRMhNQ6rCmoAc72scEXxSFwOV2QQOvKPKVpihG+ZoB9O4ilfAFV5DJGR0CimOTr+/u78OfPjyCa/+zGQo5hX9evyTjwVqxwCpfh5L1fa06gbccqFpCfC/VRhLWE/AQhbC+BJh3KWDt5EMlBg8Ab3wVeHAVUXSMx66ngYOvA5sfir5S3vBX4Bem6G14sRCeqJ0x5aspB20HaBzqs0OtkOGE2qLEr0kChRolHv6sFT99Yz9/51iHpJYDAE++VgsMuBFbQRcNbREQ9JKFtM7MK18riEqEW5DOuQhPzXgAG+kFkPfv5l+fitqj+S1g84OAI8riXQi4xQ4taOFcV6xDv83DhRuIRsbI14mBW6/s6Mby+z9C27ATpQVqXLeyDj++YE5YQFWG1EvuUe5mSc9aAMDOuT8SFR5055rpuPnEBqmPTHJolHLOGuHq5bXQKuU4qcmM/sBE5aWJcqCSIsUyo4cJICqsAlwjXMp2MoFbYlOTIxAKkQLe6q8Bt6/FZz0hyChg1fQ0kUzs/CftylcR5GuYZ3g06FT8YldK5avV5Uf3mBsXLqzER3fOBRUKEFsX3SRVvgJE6cfOnRRqMkZ0b48M2tIYAVBAgPE2bfkIeOZK4OAbxNJp9BjxvA16o6pAswKPBULHkJRgnk5+v/a+iLtllHCShgVLEurHK+U48lVogF4O2Q707CDZFM4Rcq5I7BscXhg8NhjdGoX10i1QK7hiWUy7GJZ8ZQm/fS8Cg83SHGyuIxgg57EufrdRUjAzc1Ax1gM5ZjvAZT0KfH6efM0jjzz5OjUhkwOVizAXx9Bv86A3RttJUnAxi3GtcGKIAgUZklBDioGlC9jyb6LgM9YC5Qv4x+IoX1/e0Q2VXIYQDXzn7Jl8onYOgE3U7rcmSJkWgiomubZ6CQlVYqEvA2ZdAMgUZFBfdTe5f9fTwNAhYOPfI/dD0zwhSwcJybr7ucjnfPRzsh038Y6LbNkO+OzElzkdSCZwCzSG7F6UGdQRyelSgg2Pe3ITYy9h6SQewALtOYSiZ4whX2MkzI+H5LYD48G2zhVWEKWreQZZVM86n9zPLkiLGjDm9KFFOSvyN+waRdJgf9/eJD0iwz3WBCyc682EtOkeS1L9qjYAlDz95GvAAyg12N9jhccfROeIC995aQ+GHYTEKy1Uo9ygwR1rpvFBSZlqHXUMcjd1LW8hSClwzpIZmXnvLKLSqMXWH5+JP161CKEoC7x7TjShkhrDqCLsOm2eDrjHMOZwM4Fv4lsKxaYmR8BjIeORsQaoWYa2YSdqinQwaNJUSGWVr2kNbHSRrhWhSKDsK0iT8nVLG7m2nVg4DNgYMt4Y5vk6GZWvV/wXOP8P/N81y0lh39rN31fUGDlXGW3lbw8ejPTRHzyUvmMVA3YcSgeRFA4zc50cORpxNwWIDt51eAPQq+QTvbs52wExytccIV93Pwds/BsRQISvpa5/Gbj5LUne4rW7T8S8KgPUMTz3HR7ezoFTvsYqmql0pNjAer8e/QB49Y7kPk+vI/3zCinBFt1ZD2gpwXabsddNIWA/80lqO8D6EMf6XeaRx/GA/K9/qqLqBJTYmyFHENvbUyANxoHyWsgNMYbwFKk4p3Xas/NJ4N3vk4qysRooDWsRiaJ8DYZo/PvTY1jfMoy7TpuOtd85NecUSiUFKqgVMk5BmBJY8rVmGe9hBhBViq6YWA8AwNJbeI/S8gVkQfH6V4HP/kjuG20FBhjFZMdGsn39LiAQxZc2XCWSCK5hkkoPEPI8E0i3b59Y5StjOzBk96KkIH0Jyn3hxZjXvgL8dQEhLpbeIun79Fjc0Chlgn0WxVbQRWP+lWTLFpCUGuCu9UATk9geRr5a3H4c1i2JfL1b4HU06Ac+vj9ygcEuen325I49XHUrgHytLSbka0ey1gMUlf5AOgDw2rGx24uL/r4e9799CHt7LBEPlxaGnweJE90lBRtIyEBeUIraOAFbUwmFGiUqjVroi0nBYkPpNdgqJ2NImesYZAhhtOJk/gXmJoAO4Ywjv8KP1C/zRDkLrx146OS4wY5iU5MjwJFK5NzoHHFyBYi0gFW+ptN2wO8Up3xNoOzThSkHpVS+rjsyhBWqdix+81xCyABA8XSemMxUMVVKmGqBwrDjrllOlJyWDlKUAgjBbGDIKNW4MX6wGejdDciZ69dQjqgEM0a+NpHtOEWfjBLfA+fwBCb6vQJhylehgokcUr6yn8vwUUAXRr7OOBtoPEWStzihrggXL6qC3RvAI5+3TlgHOhkSTK+Wcx7dpnh2MYVVvBocAPr3EpsNsXj3B8Cz14h/XbbAFr7TQb6yawNRXVW5Rb6yRyF03Pb4g9AoZWkTl+SRx2RAnnydqqhYCFnQg9mqIclCt2iahpxNMBWhfCWer3R6i85sW5ethyTtagxkq9RNmPyHQjRueGQLfvtuM86eU47bT2nE9NKCiQvGLIOiKFSbtNKQr9VLgGW3AYuuJSFwxYzfJfs9nvRNYPH1xLKibhVZTKy6iyhpdj8NbHiAeNC1fUaerzZEqgJbmElYuHF8NOXrCzcAb90z8X7XKFB/EnD7WmDmean/f4WA/b+nawEtkny1ewPoGnWh1+LmLCfSCxrY8yy5ueJOUrSQED1jblSbtILPK5Z8kdImJQKLmAl/LDWZkfHmLJ0Ni8sHW8G0yJRfoURk7y7gs98Dh9/j72NVsz6nuGNm4RFHvrLEU+doir6v6SRf/R7A78L6bqLWe25rJza3jkBGARcuJKQfq9IGEMbOZ4p8ZaxQWK83to36OIJp4cX4ovcnuL7rYnzR+T1YFSVA314AQPHCc/knMmTL0rF38SX6lYnexmMdwMA+UhyNhVSKL8x3tXeMkDSdoy6uAJEWcMpXS/rew+cS5/maMHCLb/N0xUlBFwOapvHp4SGcXcFc10ZbgdI5xEt+8fXAVU/wwVuTGdVL+dtsYd9Yw4+ZNUsjnz90CBg+DJTNJsXkZMlXjxXo35/4eULBjkPpth0orCRz7+Fx7dSUeNtzu9cfPfw24CU7lAtUt+eS8nX0GNn6XQnDM1NBJeO3/+u3D+HPHx6JeMzuCUAll0GtkHO2A3EL5QuvAuZewv+tNgJH3hV/UGNtpIgxWZBO8lWhJgUar4iiPB1CrlgOAODHbaHKV38wbzmQx3GPPPk6VcFMEM8uGZWMfHX5giikmUFCTOAWQ6ukjVQBIj21WDVC1WLSSj2O/Okac2FT6wi+ceYM/PvGpelrTZQA1UVarn07JciVwEV/4UOGzriPbFmFQuMa4NJ/ks/qvP8Drn+J98IESGX24BtA+3pCZtetitx/726yDW+vixZO0b4e6NrK/33oTdLK5xwmC4KaZSklvYoC59uXJoLJayeqDIGLg367Dw6PH63DznGKP2nx2C3LsaKxGKVgJpXn/Y78kxg9Fjeqi4STB7ztgOSHQqArBm54Bbg5Sio1ANSuBO74BKhdgTGXH0V6NTD9dP5xl8DfCVt0iLAsyKztgFmvgk4lT175CqSffGWUxGMowDfOnIFAiMbTmztRb9bj11+Yj2tX1OHMOeGFs0wrXxnbAfZaF65QOk5w6ZJqdBtOAPvZe5VGjjgonsYrw12GhsgX9o4LY2QtWMJ/x+OQkuezi5CvP3yvD0cH7Bhz+VGXTvJVXUgUkGlVvroApRjbAWJbEwvhnpnO8YGLSaJ7zI0eixtLjWHkwcKryMVcbyZ+8lMBRQ3A6fcB8y4DTriR3GesIX6dAFC9LPL5g82ArY88bp5OAnuSwWMXAv86STrScJxCPG2QycjceyCSOJYlIXCwewIojDZHD7jJ/ErwPnNE+er3EJs0FmKELCJRaeQtn7a3j3Et3wDg8Po5RfHi2iLMKCvA9NI4FlmnfIeINABipVXcSCyrhMDv4dcDrtHJZTvAjllsR6DUUBeKJF/pnFG9AmHjtsBzy+XLk6955JEnX6cqGPJ1mX4Ih/ps8AVST/m0efwwglE4iFK+UpAhlN5pTzj5yqoRLn4AuOaZCU9t7icD3emzSnNO7ToeNUUSKV/HY/7lwI8HgJKmiY+ZpwP1qxnfLubzKagADrwOtH8ONJzCq8DkKjLJZsO62tfz+wknX1s+Arb+h0y62AlbwEuSgT/5DQmlSPeCYDw0aQ4V8tpFWA4ADm8QFHOWpJN8PX12Ge46dRoaKOb7KWlKC+HdY3EL9nsFEHYupvFK0XRWpCVJ5AEQhTgAi8tHQoNO+Q5w5s/I40JtB2ws+Rr2++dsB5IkX0XaDlAUlfq1Q1sU6cUsNZh9j9GFOHVmCZbWk/NxZnkBivQq/PbyBZGKp4wrX4cAmZJXvYkJEJwiqDfrsfGHZ3LtqAG1iXmE4oknAL/4ZNy5ceT9yL+9iclXsanJAEhgzdvfIe27AAZpI3Z1WgAgveQrRTGBjZb0vYfPKU75ivjKPl0alK+H+6z4luJlTHfvI3csvBo44SZJ9p1ToCjg1O8BVz3OF+SKp/HnQBVfoABAlK+2HqIANdaI83QMxwDzuYZ3FKUC9nqeRrUlh8pFRCUf9psknq8ibQe8ARRGtR3wiguqShBIlzGMtSNijpNGCwhW+QoAvmAIj25ogzdAzn2HJ8CNr7MqCvHhPafGDtwKxz2HgG8fIAGtQ4eBnxuBPc/Hf82mfwD/XEUsmdyjxDLCn4Z1TTqQTuUrAKgLRBblaeSS8pUft4U93+0PQqPKk695HN/Ik69TFSo9YKpHXbADIRrolyB0y+YOwEgx5Ov/s/fecZJc5fX3udXdk/PM5hy0u8phhbIQEkIIgYgmmSQwYIID2MYGY7/mZ7ANxjZgcsYmmZwRAgmBUM5Zqw1abd6dmZ2dPNPdFd4/blV1mIo9XR2qzvfzkXqmu6e7dqZv1b3nnuc8YTJfbefrog/BmdxMwaUEyLgBQJa79axc8PQnTfF1y7Lgwli9WNXXjtHpXOVdy73I+GRltXTICdbQFmDr1VJAnT4GbLpCuloA6YJdeTZw5EG5EP3DfwLrLpF/g2Lx6RsvA375N/Lr7IR87uRhWULzhNlgwCGbN1Jq4XwNIb5OztdGfAWApd1tWK+Yf5+BjVV//fm8hrGZHFb2+nzGigg7iasmjx6agK4bMAwDB8ZmMT6bl6V4g5uAi/5CPsnpczI/uTDv2Mv5GlZ8zc8DP3hLYXMDCLxYW9bThuGpRSzae1YCEwf8nxeSibk8pubzdgnsCaMba/o7cPWpy31+ssbO1+kRmYk9ZDaPidLl2OAMmotyw9qwGtoirw+nvAg6FNx6uOxvUh4vYGUde4mvAujBDDLTB12fs4DvXwfc8yXgwW9Ch4Lj6MVDB8cBRCy+AnIOFKnzdS5c5qtf7ECR83W2Spmvx55+FO9K/xC9B28GVp4DvPQLQNeSqrx2w7L0ZOBNNwBbnleoJFqyVZ4rABlTMj8hPxs9K+VcaHrYORc/KJVu2pUzdVS6qUOJ+hWy4kw51ysyRihChL6+D09m7fNPCep8iLxX+Dakqxnlne0jFMKXFTUQbsso+OgNT+Lzv5eN4aazGjqd4hz86Fkp5859awvzA6snhBvH98j508iTheiLZnG/RtlwC6jQ+do40o0IWbEyT+crIRRfY82SbRiclRfairteFzExl0efLb6GuBBZma+LPgIX7NIXc3HuILgW8+TRKawb7Khs4lFjVvVL52Ak7tcgXPEP8r91l8imTBCyKYDlvutaKifZ08eA3/2b3NW++l9lMP+0Q+yAxfh+Kb4CcoIOLCzdi5qoG27lpmV5VgDm8xpmchoUc5RE2XALAJZ2t2KdOAZdpIHetVV//RFT9Cue/PtRKF+qLbuHp/GCT96Knz18GNc/ehSX/vvNUHXDbkKBVFrmm1mLhps+KB3bx/cAH14DfP+N8v65E1IwmSpzvmpq4TMWNnZg5Angke/KEmTr/BbQIb60uw0jk4vYdDM72Nv/7ipx2UdvxvYP3mg7iadTPRjqasWLz16FZT2t+JNLXDYDaul8/fpLZNZ115LC5kR/jTeHGohB63xknTNNhzhe/j/4/St34LhR2GQylp26UGAI4HxVhMA/pr+Orb96jXRIDT/h+XxMHS1kkI89hZl0P3QoePig/JlIM1+BaJ2v+TlZDdIWptTVu6y6eL4zk63OZu7IsaJrfF/1ryMNy9oLZLXIlucBf3qL3KCxmhEVRzL1rDQrsQxg6nC49yg+z4VqyOPBsUeBZadW57X8WHGmvC3aOBQinPN1Pq/h8MQc1g85xG+Edb42SuzAcenSh2KOxwhjB1qKOsp/560XAgAePjiB+/efwOh0Ft2LWQP1rSt83V22cVqebW813913G6Dn5dfF4quuhQ8DrhWRO197ZCb0h5YDh+73f76hN1jsgLwNusJn5ishFF/jzdJt6JjcixQ0HKyCeDc5l0c/pmTpoRLi5CmE2XAroomPtbO+8ix569A4yDAMvOlr9+ALt+zBjqOT2NoErlcAWG1mZr7t6/fhyEQdBNgzXgGc8iJg/cXy+1XbpeBqxQ50LQfWXSS/vuvzMpJgxZlyMmaJT06Oj323A8OPF77vXlH1hk++tPUCEBE7X4MtnveMTEOHiN75evBe4ImfYbCrFevFMYy3rpDiYpWxHJdh/h125mtkoa/O7B6WroO79o7hO/cUnJ69xZ1/O/qlWDj8hHR3P/4T4MtXycd2/FwuNj5+BvAvy4GHvyPvtz7/8+OwF33lDiYtL8VZNyaL3LNWiWtQ8bWnFcNT2cp/n1ZTvrGnKvv5MiZm8xiemsf4bB45Tcf4qPz9tPcMQVEElnS34q6/vxLnbXBzAtXI+WoYwJ7fyq91XZ7L/vh7wEs+F+37NjDnmpEQrTCd1CtN8VUInLGmD/NoxZwhNyvEhmfJzbX8PPA/1wIPfKPg7CkXU8f2ytgZw4AAcIHyBNqm9wPffYMsU/3R29wPqljgNXRMpOXnZuexKXS2pNDbHnGWe2tPOMdSGCppjORTVl3ccGsur0Grwnl28niR+NoZc8erE4pSEBm7ZZNArL2w8LgVOwAAE4fk3+d71wGP/cj/tYvnJfd/Hfjth9yfq6myQuLwA+7P0XUZA2Adb9QsPUUKjEcftu8SQoQ6ex88MQvDANYPOomv80AmeKxRwwhWxx6TbmirmWeEsQMA8MEXnYovvf5cnLmmD88/YwXufOo4XvqZ2/HggXE787UiijdbipuYHrgb+PDa0modS3y1rqtA6ef7nweAH/xJ5ccSJXbma0RrxtZu2YRMnVu4aelIg8UOhOzVMJfX0M7YAZJwKL7Gmf4NEHoeK8QJHKxC06bJ+TwGxCSM9pDZnKIgKkXCCbNz5mXvlSXCDoLXnU+N4bc7hvH53z+FvaMzOG1VRLuYVeasNX14zinLsGt4Go8c9HABRU3PSuCs1wIXvF1+b3UwtpyvZ70GgAFsv07e37284ACcLCojtRaTv/q7QgwBUNpNuFYoKeksikp8nTsRuDHdnU+NwYBAR4s8JS+Jyvn6pWcD33ktUoaGU1IHcSwdjeA9Uon4at7W2puyf0xWBfz6saP4w64R+37b+QrI0sDZMeD3/y4ny1f8o93kB0Nb5aK33J00dUQuts1O7ABKna+GAXz71cDHTwf23SHv23UjMGJ2JT7ycKErMiA3QS75K2DNeYH+Xcu6W6HqBk7MVljuajXjq7RZTBEzWRVn/vOv8cJP3mbf9+ReWbHQPbjM7cdKqZXz1VooAoW/6ZarIl8kNzJ/9Zwt+Mp152IQ4/KOotzkwa5WrOprxxi6obf2mPmXhowe2HsL8JN3FsZKuVP0iZ8Bv/8IMHEAmblhrFHM8bfzV/J27CnpivriFcDvPyrv232joyN7TMi/T1bVsTSE475iWrur50gsp5LGSAKeZdVWvqPV2XwuTJTREz9fkOOrajqyk0VxT43gKqwnPab4uvpc2YwNkBtmVgzW6E75eX7sR8Aj3y/83IF75HXh5n8FckUVasV9DO7/H+Deryx8z8d/Kpt7Hd8tKyR+8OaFz1Fz8lpyYq+M/6iV+Jppk7FUU4XzqUzGCP45eXpU/j7WDTq42CtyvqL2uUaGAey/q/C+Rx8Flp9WmENHnL/7ugvX48pT5DV267JuTBc121tU9V+x+FqcDf/0HwBdBR76TuE+65pa3BPCmnfr5nnosR+Wvv7UMeATZ8qognoyPyHXlGEMR2EoFnWDbOY1WOyANa6Cjus5xg4QQvE11phOqVO6pqsSOzA5l8cgpgqThoAIWM7XRR+Cy4EdBFKtwJbnAld90HGH+6u37QUAHJ/JwQDwkrNr7LKskExKwQdeKMvExmYWkRlWDV78aeD0P5JfW4tCq9zo6n8DrvkPKRABhdyzo48UYiG2Pl82MCom0ylLujc+K/LDdyTKju7Tw4HcQPN5DZ///R4MdLaity2FNQPtWNoTbewAdl6PjTiIh9KnR/LyI1Oy3H1pKOfrIrqdV8j+47N4akSWyI1O50p27/tLnK8DcvH8xE9lt+vz31a6yWNlXFqfYyUjy+tmx0oXJsXO1903Abt/IyfcX3u+zK78zmuAm/6fdIZ//lLg1/9QeH7PCuDKfwq84LQiH45NVpj72r9eTvLHFi++fuImWWp5tCgGYWLsKKbRjuX9QUurayTPW6LH6a8AXvn1aN+rSUinFFyxbRnE1R8GznhVqbsPwLVnroTRNgCld00hB3Pv7wtPuO9r8rbc+Wp9P3UUPaNFrj3DXJBPD0sh9tB9wN1fkELTN14G/Op9hfO2Wf46Kgrlu5FtXhUTpfPVau4XSpjxLqvubsvg4688C6+/cD0AuSESmN99WMYKaaotlty6exS9uvn3u+CdwGV/F+JYY0jvanm+7F4hz52APGdbFT0/fxfw1Wvk14cflLfHHgO+fCXwb6vkJsQD3yi8XrH4Ontcft6LS7O1vBRbb/9v2RwQKFyTDtxTuJDe8lF5LXnwW/L7WomvgDm/KmySKN6xxAt4+ri8Nrs6X8NmvgK1F18f/CbwlaukuP7pC2SU0LJi8TW62IFyyvtcdC1KfF1T+Hp6WG4E5Oek0A/ITYaRJ4Eb3m9+PkXp/Mc6fxfPj4qbcI3skGPg0H3yterVLG1+MrrIAaA0mqw8rsGJBosdsIdVwOfP0/lKCMXXWGNO+k7umMIP7z+El332dty9t/L8vvE56XxNhW2oIBRzWRDRxXPikHRmmleBkaksHjtcWOTtPDaF3zxxDNddtB4taQVXbF0afR5cFbGaDRyvt/haTJfpVrPyddt6gfPeAqRMwer0P5IlZ5+7BPjhn8r7rv434MJ3AktOLrxOaxfwroeAc99Uu2Mvpr0/mqYpuiYnlQHE1+/fdxDDU1lsXd6DzpYU/vC3V6A1HcHkRC9yOt34AQDAr+ZPdn7uIhmZykIRRVmRASisjWozyT4wNosr/vN3+L97DiBlBle97JzV+KPt0qlUUpLX3i+bS+gqsP0N8nP72h/ILOS5MRnn0LdOZgAChTy3sT0F1x8gFx+6LhfO93xJuqL+8iHplvrle+SC8sBdwM/fvfCAvfIvHbDcf8emKsx9TbcAvWvkYiq3uM27m3cML7hPzJ3ACb0reFO2Wi2eLdHjsr+rrVDRDCw7FXjp5+Vno4j3Pm8bVl/6GuCMlxfE16eKxFdrgT0/IRfT/7ISGN1dJL4eQc/wvcgZRee9lefIsXXHp+VmxsxwYTNifqIg6iyXG0jDRmGBvCTqzSsgfKOUMFTkfPVXtl589iqsH5Jzn1Di69RhWWH0ledK4RvAD+8/hBWZaRiZTpnz3rU0+OvFkWe8GXj9T+S1YXCTFEJbu0tLsq0c/MmDsiJiuuy8qBQtyexeBiaGXsjHB4DRXTIXeOIAMHlI3tfWK8fdl68E7vyMvM+Kjbnni0C6HViybfH/1qC095c41AVEqMzXfcdn0dOWRl+HQ4RIpc7XWju0D9wtb+/9ihReAel87ai9+Lp1ean42r2Y2IHWbuDa/5ZznvF9wHdfJzdojj4MtHTLc8b33gjc8Sn5/NVlPR0s8bW40uTwA1KsHd5RePyh/5NRHeVNHGvF/ES04mux8zVwY73GEV+VkOorM18Jofgab0zn65Aud8WfODKJt379XsyHKTcrYnQ6iyFlCkpXOOdrIfO1orf1Z/JQIVcLwEd+tQOv/sKddqbZp367G+2ZFP7y2Sfh2285H//20mjcflHRlkmhoyWF49MNJL72r5M5iKe/3PnxjgHpHAMKCw4rs/JttwJv+Jn52DE5+YyqpMeDvKbL/OIonK+zYwAM3wWpYRj43zuexumrejHY3R6tsGQ1OAOA47sxm+nHLRNLKz4feDE8lcVAZ6stagah1kuj7917AKp5jrj6tOX4wuu2499eejr+5SWn4YuvPxfblhc5Mk95EbDsdODs1xZKrtecJ/+bOyEXBqvPBbZeLR+78J3y9itXS8GotUc2bMpOA3/4D+CT24GD9wAbLwM6B4EL/6xQMjwzIl0f5bT1hfr3Wa7jkUqdrwCw4gxg5/XAv66wBfuwTMzmsWt4GmesLixgti7rRmZ+DCfQhWVBxdeaOl9FqbOH+HPJu+V/bb1yc+7AnfJ+pWiBPz8hS9jzM9IZa5XtTx5B/4Hf4Db9NOTazA2rTZfL2323y3HXuVQ6xQG5YJ0dkxUvZjzGEa3w+QrjuK+YNtP5GkWjmIozX/2PpaNF/j1mcwHP+2rWdF6OyfPc4z9BXtWw7Imv4rKOvRCdIWOo4kp7P7DhmfLrc95QuAYAhXxPQFb6ADITs1x8nS+KsZhzMEoUR20ce1TeThyU/wGlMUpWibcVlzI/AWx+9oKNk0jpGFjofA3x4/vGZrFusNOuiikhtPPVXO7W2kFpbe4Xj83lZwDLTpHNHGv491g70IGXnr0Kz9wiz7HKYh2U299QGoN04mkp9p/3Zin0Dz9WeOyk55b+rC2+Fo2Bh/5PirU/eHPhc2P1hpg8JD/nd31+ccccFit2ICqKXztIQ1bDaCznq3kbdFNlLqehjeIrSTgUX+NMWy/Q0oXLV+TxugvW4bOv3Y7x2Tyuf/QI/uZ7D+HTNwcJ9y5wfHIefZgq7NgGRkARRuBA7kCc2Cc7Uk8dlaKSJewBePTQBCbnVew4Ook9I9P4+cOH8boL16G/swXb1w3UJg+uygx0tmBsZhEiShRsucq74cE1/y6FVgursVMqDawyd8EtB20IfvHwEXz2d4VS6N3DUzjm0tV9Jqvin37yKCbn8wse++RNu3DzvjyM4kzOajFjTih9IjoePjiBncem8boL1skFRoDFc8WckNEbuOjPgZNfiN2n/iV0Q8He0QClTiEZmcqGFkAUpXaxA4Zh4Pv3FbKIW1IKrjp1OVrSClrTKTznlLLP5cnXAm+/FXjRp0vv7xiQbtjJQ7KUsH898I/HgWf/I/CW3wJbnycdTNd+QrrEczPAk9dLp8jsaKFr/JarpdBilau29QLnm/nK214gNzrO92g+5IAVXeE2NgLxki8ArzLLVS0HT0ju3y8XWS86q3COPn11L/rENMaNLiwPej6upfO1Z1VIVxUpYfkZ8lbJyMY7Fnq+kB16+P6C83XXr9E2fQC/0s/DXPd6uSC1c8AN6dZ78WcLrzMzIhfvHQP2xushtVh8rVHmK4wQbqUQWM7XUK64YN3cO03xNbDztdiZBgOYPorpn78f71f+B2tnH69gPpgATn4B8Kz3Fr5/xx3A+w4Bl/8DcO3H5X0PfVu6A4spnovMT5aWJAOl4qvVyGriUEF81bVC9ZH1WsU/c/ILK/rnVEz7QMnmthAiVAPIqfm8s+sVkA39wpyj7b27COdYTli//7kxeT58+dekM/qCdwLvrOyaWikpReC/XnkWnnuqnN+MTldhTVFc3TVhOrDXXFDYiLZYf4kplgs513ESX/fcLG+VVOFxK1Jj6qhsZnr93wIzRVEFUXLrx4F9t8pNjagI63w19IbKfA07LWPDLUIovsYbIYCeVVitHMcHX3waLt08hPWDHfjc757C9+87iI/e8CRe/5W78cVbgnWznp8+jhT08JmvlvO1mo6l2/9bds584mem+CqdBfN5DbuH5QXsD7tG8c8/exwtaQVvuXRj9d67Dgx2tjRW7EAQWrtlSehfP7lwktnSAbzi68Abrw/9sl+/82n89027oGo6DMPA6798N/75Z487PvfuvWP4nzv24fbdCydrDx+awJ3ZdRAn9sps2mpiTRh9YgeeGpWf1XPX95sTqgiFJav88BlvAV75daTPk91l94xUXzwYnsqGarYFhN9Br4RP3LgLP33oMPaPzeLwxDzeePF6AObvvxKKMxkHNshba5Nh1Xbgld8A3v04cNpL5UJ6+lhpF2BrEyLdArzh5/K/ruUyV3blWfKxnpVyo8N63YC0plMY6mrBF255Cjc8dtT/B5xo6QC2PR841dzoqoD79p1AShF4wRkr7PtOXdmDPkzjBLrtbFp/auB81VT59+lfF917JIGVZ8vbjoFCLriF5YY6VCS+7rkJhlDwG207jmx6uXQNFm/MDWwATroSePNvgbUXSWFp7oQUJ82Yg525wrwk7LmnIqxFcxTRA7NjcgMmzJgPEDsAAB2tcuEb2Pk6eWTBXf0PFgnhAaJ1Ek97n4wjuOw98lpw6d8Aj3wPuOU/S583UyREzU/IMSCKhIpiN+xR0/mqZYEjD8qvc9OFiBhrDmLF3rQPyL4ItcTK1Dc/lyKk8zWv6cikXJapYZ2v9YodGNtb+Hpwk7yWAjJiIuUiLEfMWjN2rTVdBQmgePxbLtW+tcB5by2N7elZKTeo23rlho0lSluf+RVnAhNm1EZb78KKtKmjhZ+JIiqsHMMAbvwn+bUeIqIlLKFjBww0YuxAkFGV13TkNYOxAyTxUHyNO72r7DwoRRH4k0s24MljhcXCbbtHcfOTC/P4nNCmzUlcSKeDUe1GOnMnCs0DHvuxbM5h5tvuHp62S4k/8qsduGXXCN5/zckYqkUDjgiRztcmE18tupeXdMe2OeWFhXzAIo477MYbhmGXxz81MoO5vIYdR6dwZGIehyfmSzJ+i7Ea/Bwen1vw2P7js/iedhnUVHv1S5ks10mnd+zA4XF5fCv72gGE7EYRlPlJmQO3/y7pvDCdYhuGOiEEsGe4MZyvYYP7w2IYBj524078xbcfwPWPSiHxpWevxj3vvxKvfsZan592oaNIfO1zEOyEKDRcaekEju+S56uWbrlwXHZq4bnLTpGl7u+8C7jyA4VsvnLxKgSff912aIaB23cv0t3dtWxhiWxA9o3NYlVfO5b1tKG3PYOhrhas6mtHr5jBhNFZgfO1osPw5pHvA7d+DPjN/ycXkGe/NoI3SRDWxsHsmPM5cMMzZbSGlVUJYHbwdIyhB0c3vES6BosjWwbMzdPV24HBjfL8OjsmBaWNlyP35t/hYbUQE1GT2AGrXDQS8fV4uMgBIPDmneV8nQ7qfJ0qiK85I4UfaJfi/9Rn4XuqWWLf2uXyg8SVK/5BzqNzU/JztOw0GUcwMyKbDg0/ISM52npKxZni5kSjuwpRNIfNZnXZKRnpARQ5X4/Lyor37JYicC2xKkPMeBEBEWqKk1N1tLiKryEzX+vRcCs3I/N9LRpko+KSzUP4l5echr97XhXyf4v/TXlT+O9ZAay7CPjTW4CNZnxM1zLgtJcBJz2ntNHt9DCQ6SgValu7gdky8XX6WJH4Gi7/PhAH7gEe+Gbheyuma8WZwBX/WP33syg+fwaOHYjucColiGnCWsNRfCVJh+Jr3OlZVSgFAfCKZ6wpWexquoGdx4I534QtKIVbFAihQFRzxfzYj+VFfmirLAkBZOMaAI8flpO8CzYOoKs1ja9c9wy8zuzu28wMdLY2r/gagocOjOPcf7nRbtBz374xvPZLd+Gzv9+Dbf/4K9y+exTDU1KcfWD/CTywfxyAFHhmcwsXk1bJ9ZEJKb4+fngSf/+jRzAylcWBE7OYRBce77qwtDmMD4FKtaaDxQ4cGp/DYGeLzEAK6FwKzR2fBv73hcBD35LlkGa+bntLCqv62iNxvo7N5DDQFS7LTNibNNEsjo4VZZ9++PodSCsCW5Z3YUl3qx15EJpi56sVGeCGNckWCvCqbwAv/JSz86W9T96/9BSZqVyelRaC7esGMNDZgqkwzXWc6FomhYIg3XjLGC0S4tcMtGNJdxuWdbeiG7OYUzrQ0x7U3ReRc8kwgN9+EPjth4D7vgac8UrgrD+u7nskDcv5qucBq0GnlXUJSFeUoZc0FZpecSGAolOgLdoK6aSy6Fxixg6MybEiBKb6ZLSB1UBmaU0ablni66T38yph9njpuSUQwWJrrDLu8bmFUTyOmOKrkWrBHmMl/jr/drxXfSvubbtAPu7gjCU+CFHYeFt+BvD222RZ9tFHgH9ZAXzmAmBkp3QAloivpvhkGFKMsqM5TLLThXN0bko+b+a4FHrrkKtvf4bN45ZTnODn75yqo8XJnXniaekSbHTn685flX4fsmowKoQQeM3569DTVgXnbUdZ1VC6rTSf/lXflPFjmTbgwncAL/uS3Ew79qiMyZgelud0M7sbgPzbLnC+Hik4v6t9ztU12aTuJ+8o3Gc1R7vqXwqbiVFQ4nwNMr8ymjZ2YM4UX9sYO0ASTuOMYBINQ1tkWcf4AQCyFPUbbz4Pb7p4g/2U0emsr7A3n9fQljcvhpVkvsKonqjy6A+AwZOA895i3zXXvhz37z+Bx49MoqMlha+98Tzc9ffPxuVb49GBd7BLxg7UqhN8vfjN48dgGMCnbt6Nncem8JMHD+PW3aN2NMYff+ku+7n37x/HA2aepGEA37prP0amSoXRY7bzdR66buC9P3wY37prP5757zcjr8nf5eNz/TCmjgRqnHLHnuM490M34qYnjjk+bv99ZkZko5myJkkTs/mSv+Hh8TnT9QpzFhPB39eKG3jN94E/+mrJQ5uWdFVdfM2pOnKaju7WcGXy9tIooo+4lW27cYnsPr20uxWt6UVOAoudr375jBmz6/XGZ8n/znBpVmeRbpELleWnLeYI0dWaxtT8IsVXy3077fy592JkOmtXHvz5FSfhL67YjGUdGtJCh9Ha69xMxYmonEtHH5GLeV2VrrEzX13d108i3SuAJScD1/xHIT7A2mjYdEWpmGoyvfIiACjEE2XapPjUu7rU4dYxJEXdE0/b48/6fG9e2oWUIrCixyOLvFrYsQMRiK9zYxU4X4Nt3g12tkAIYDhIFvTxPbJBWqoFExtfiBv17XjRWTLiaW7IbFw62NyRTnVjmXletwS5riWms9X8G07slwK/k/N17oQcA8Xiq0iZsQNFAs7UUfkz9WqKZl0fTSFNEQjV+yGnOsQO5GaBT5wpx12ohls1cL4aBvCTPwP23yl/9z96u/wbnXSVfNynEqopGdgos+G3mBmv3StKG0K1dMr4sWI2P9tsVHq/nFN0LQMGiqrg5iccxNcqOV8NQ57XinnsR0XvbZ7Ph82mp0tPrvy9glDccCsXoIrC0NFI1tdC0zb/cZXNyzVWWzXiLghpYjgC4s6258vbuz4HHJN5PJuXduPizaWTsZ3HvE/6x2dyGBLmRSns7q2V+VqNOc/0sOzievofyRKW898OXP5+fHVPB/7os7fj9ztHcPKKHrRlUnZX3zgw0NmCnKpjJmhOWxNgGAbe8c378Lav34dzP3QjfvTAQdyyawRCyJzIqz52C37yoCz9OTGbL5nPbRzqlM7XA+NYZrqcPvSLJ/DGr92NvFYQUY9OmOLrxBx+u2MYDx+cwDWnL7d3YK85fTken+mC0PP41u8ewPWPHMHtu0dxy84R7Du+cBd697AcJ04Zmh/46WPY8L5fSnF1ZkTu5isKdN3ArmNT+PTNu3Huv/wGH76+0Mn+0Ik5rOyzFhARNdyaOAisu1iWe5UJXZuXduGpkZlQTTD8sBq5dIYVX+3sqGgWR0+bf8+/f56cTIc9PkeK3Wl+IqLVnfqMVy7+fUPQ3ZbG9GLFV0tAmwovvo5OF/J/n3vqcjzv9BUYTMtNklR7r9ePlhGRc2nHz6WTpGeVFPbWX1rd108iQgDvvFNukFplqctOBS5/P/CyLwO9hYgApORnY265zD8umSd0LStkKVtYr6fO2+PPKqF/48Ub8ON3XIxetyY91STqzNew4mvAhlvplIKhrlYMTwao4PjxO2R1kZbDw8/4MP5TfQVefNYqZFICAys3AX9yI3D1R0IeJwEgY2YA+TkGnEvSy2MHLOeflee6ZKscA+suAZ7xZvlZLM6NPPqwzIQN/VmqEtaG5JzlfBWhru85zVjofLUybIHGc75mJ4EHvi6vKQfvkb/7qz9iRz01SuxA1TnzlQXxtHuF93MBuQEnFOkMnjggI2aKna/zE6X5xgAwfbRwX7n4OneitLGcF0/dDHzyHOkst9h3W+FrK2ZlZIecD0TtVg7rfDUM/7lmDbEOJcgSImeuzRzd7IQkCI6AuDO4SZbD3vEp4LMX2ncv7y2dtLzqC3fiY7/Z6eqsHJ3KYq04Bl2kwjtf7YZbVeDYYwAMmSfUMQA878PAZX+LRw9PQTeku+2UFRF2pqwTA52yhHtsOj7RAyPTWfzykaP41WNHkVM1fOCnj+ORQxN46zM34k8vk26aiaLSyDdfUliEv/jsVXj6+CwePDCOFxd1UX/00CS+cMtT+ORNu3BofA5HzQXm4fE5/GHXCDpaUvivV5xlP//dV27BRFpOiH9x42/wwe/fjnd/90G8/it347qv3gOgtEyu1cwquvOpMbzlf+/FgbFZPHpITgS/dvvTAIAjE/Myb61jCIZh4LVfvgvP+dgt+OgNT6K3PYMv37oXu4enYRgGDo/PYVWfbH4AoUTjypg4WJj8l7FpSRfm8hqOBHFBBWS6UvHVvI3KmPL06AxaUgou37YU//yiU/GpPz5n8S8aJkPvvLfKbDNrQ6xGdLWmg+c7ur6IKb5Oh2u6NZ/XMD6bX5C5nclLgaC1qy/4i1XzA7L3D8D/vUaWGx68VwqDf/QV4GVfDN3YjPhgCQ5aHrjsb+V1u9glfuUHgPcfhZGRsRwli7irPwxc8f+VvV7R/MN8ncl5eZ1Y0tWK01eHEfQXgdUBez4C5+vsmL+TvhyhBNaVlvW04tiU/zl/ctoU8rY+347bWT/UiW+++QK84/JNwJpnMPO1UvrN+YxmzumsjbzlZxSe09ZXEGfaegsCk1WB0LkEePdjwHU/l8/LTZfmRu74hbwNXa1WJezYAeliDJuslFO1hU2hikW2UJmv5utE6Xy1RMGpY+ZaRUiR3ToHNkjsQCRY/7aeAOJrx4Dc5PzDf8rKrC3PlZtsLeZnfW681PmqpKWD24rzKhdfP7Ie+PeyTTo3RnfJ27Ei9+tMkaBvZb0eezR61ysgqzif/U/AydcGy3xttNgBBO/pYhljXHOcCUkIXGUkgcvfD/zQLNGfHQM6BrCiV5blLe1uRUtawZGJeXzipl1oS+l4e+aXwKkvLjS5AHB8eh5XKfdiesVF6EmHzXJUpCejGnOeE2bn0KJjA4AdRwruk1NWxk98XWKKF8NT81g72FHno1k8jx6asMvdv/4n52GoqxUv+cxtOGVFD667aD1W9LbjyPg8fvrQYXvCvm15D153wTo8eGAcF2yUTg5NN3DBpkFsX9ePNQMd+NdfPoGP3vAkAOnWtmIHhqeyuPOpMZy9tg9tmRSuPHkpbnxiGJuWdOG5F54N3Al8s+XfcIt2Ol4/+T4AMo913/EZvOQzt2PTkk584lVnY9IUg/ePzWL/2Cx+87hcBN34V5chpQhouoEHD4xj5fw40N6Hxw5P4vY9x/GmizfgtResRU97Bud+6EZc/8gRvP7C9ZjJaQXnq4jA+aprsqmNq/gqS+H3DE9jVV91SnUtoa8rpPhqlS9V0YRbwt7RGawd7EBKEXh9tXKgrRy9c9/k/9xTXij/qzFdbRk8fXx2cS9ixw4Eb7r14et34HO/lwucBd3nTcHquedsCXEQVXQu7bpBupOmjkiHy/pLgLUXLP51yUJazLiNfNFnUAjZ/E/Pyw2MTDuEkCJUyQbw5mcvfL1i95hZ1jwxK8/LVuZrTYjK+armZPxFaPE1+PVjaXebXRXixdPHZzBmnIlTrvkiRh+SGy9DXS3YMNQZ7tjIQtacLzfkzn+b/F41m4Juulw6VoHS2IHBzUXiq3ke7loGtJjzwdZu+fefGQF618rvH/+xfKxeop8dO2A6X8M23NJ0ZFJlLr9iR2SYJpB27EAE1UUWtvh6RJ7vBjfJ858lfsfV+QoUPmNBnK+ArID4yTvl7+js15nVEncBd30WuOMzUmBs7QWyE7L56LFHCxEvi4kdsJo8WiIrIMdV9wr5d5s6InOSDz8oGz9GjaIAl/4V8Ku/B/bc7P/8hosdkLdB7FV5VT5nQZQIIQmD4msSOOMVchL37VcCv/8IsPRk9J/zBrSkFazub8e33nIBMikFf/at+3HbzT/H21MfBG76f8Bf78TuuU78zfcegn70Efw0dQxjW/+qggMQENCr430de0qWKXavhKYbuH//CZy6sgd7i0rE4+h83bREukt2D0/j3PVhG3E0Dj958BC6WtP4k/+5175v05IurOxrx4P/31Wy8ZTJGy9ej0Pjc+htz+C3O4Zx0rIuvGy7FBHnchrSimzjdu66fnSbjQP+4tkn4Q+75C72gbFZjM3ksKqvHYfG5/DksSk897STAACffe12TMzloSgC11y0HbhTvuf5qR1YkjIwMi9gGAb+/NsPIK/pePDAOP7njqddM0J/eP9B9He0YHQ6iwf2n8A12Wmgbw1+/MAhZFICf/HszejrkJsWy3va8PTxWewZleJzQfSMIPN1+hhgaO7i61L5ufroDU9iw1An1gwsXtivPHZA3kaVa/z08RmsH4xANPhABJ13q0h3WxUyX9sHpPtkKpjzde/ojC28Ag7ia1b+zpYtDZGBV83MPqtJ0LHH5GJsSRW6PhNnhuQ5Fxf/Ren9rV3S3dQmnar2n9fv9axzWboNOOkqzOc1fOKmXRjsbMH6WoqCLabjMzslF/JtvQWheTHMj8vb0J3pg18/lvW04uGD3uctTTfQjVnsxQp85vdPQ9V1tKaV0JtqxIVUGrjmo4Xvt79R9mZ45nuAu78oxTsrdiDTKaM6DtwFaGohdqCr6PxpOZCnj8nP4fpLgLs/L++rV+yAlXlvZtUqIlysUN4xdqBIfC2OIPClBrEDc+PyduqoLKdfcZb8vjMB4qslMFsbtX50LQFe893S+3pXyVxcQ5P/DW4EDj8ArDmvENsElFYb5EJuLFuia/FcZnZUZjBPHZHzgT03ATAKWb21oKVTxg7ouhRk3YhB7ECGsQMk4XAEJAUrT+euzwG/+zCEENi8pAvblnWgLSWQUgT+34tOxTNEIQdn/t6v47bdo3jwwDiuUB4CAPSc9eLw7y1E9ZyvY3tljIKi4EcPHMLLP3cH/uOGnaYzshvtmRS2Lu/2fZlmY3V/O9ozKTzpk83b6Pz7r57Ep2/ebX/f0ZLCCjMCo1h4BYCz1/bjB2+/CJdsHkJ7JmUL0ADQ3pLC6at7cebqXlt4BYBnrB/AV697Bi7ePIjf7ZQLlGefvLTocekmypi5dwBKFjCtyOP7L2zBe5+3DXnNwMMHJ/De523DeRsG8LsdI7bzFQD+7upteOAfn4PLty7BD+4/iLEZWZZ5374T0LNTyKU68OMHD+HyrUtt4RUA1g12YN/xGXzjzn1oz6Rw4SZzYVTt2IG9twD/ZZZN9TiLr4OdLWhJK3jk0AQ+87s9js8JS6XOV4solka6bmDf8VlsGGp+13hYulvTmJoP2NncDUWRLquA4uu37tpX8v1QV1m1hLV4ag2zUVbFxbP179j1a3lbi/LCpNLWKzcoTntZ6f3F5dQoLl/0+ft2DADvfhx47wGgezlu2z2KHUen8MEXn1ZbYVBJyTLZuRPA5y4Fbv7X6ryuJeCUNWv0JcQka0l3G47PZKFq7i7AvaMz6BJzmDba8bXbn8Y37tyPoa7W4A3ySDg6BoBrPy7HhSXWtfUCZ70GuOIfZFb41BHZHGj62MKGnlbJ9tRR6YbddIX8XsnIOXM9SKWlo3DiIAAp1AStbNF0A5puoCVVtuFtlaM/4y3Acz4Y/Fhq0XDLcmQe3y0bAlpN1U66CrjiH0sbpMUNS1gO6nx1o60oNmbFmfJ22wtKn1PsfLUaygKyr4nZXNoVW3wtcr7OjMpNvfZ+uTG781fy32OJ57WgtQuAUVoh4oiBRnK+Iuh1G4XYgQVudkISBrewk0L/OjlZ01WztOIYvvGGM9D3P5cD/zkJXPvfWLrtGrygfz92nliFabRj1X3fx/5t16Ato+AvT54Ahjch3RtwV7MIUc3M17G9duSA1dn+K7fJKIJPvvpsZFLKAhEvDiiKwJZlXb6N0RqZqfk8Do3P4fhModHHpiVdvou51124Ds87ffkCJ+WnXTI7L9+2FI8fmcRtu6Xb4qXnrMaLzlqF23aP2nEFJSiln5d1Uw/hsi0X2I2xXnjmSszlNHzoF0+gz2zk0tmSwnNPXYb+zhY855TluPlJKfQu7W7F/fvHMdF2AjeMTWA0l8Mfn1/a2Xv9YCe+c+8BPHhgHK+7cF1BmK127MD9/1v42sX5KoTAd956AV762dtxYGyRpekmM1nZzKzS2IEo1kZHJueRVfXaOuMahK7WNLKqjpyqL67RQd86uaAMwO+eHMHFmwftMbjQ+WqKr20hxNdqLp6thRfF1/phCe8Z6fwP9eftLeR8W1mkZ9Qq67WY1m7ZAHR2FDgiN6jxxM+B9ReHjw2wsJ2vFWS+hnC+GgYwOp1bkP9v8djhCVyNOVx1zkkY79+Kj97wJA6Nz4U7JlIZnUuA8f1yjKy9QP6n69Kh/+O3yXl894pSh5y1mTF9TM73tzwXePsdMkszU51IoYro3yDn7ZDX+KCVLTnVcsmVzQ8t5+vV/wakwjTWq4Hz1Rq71ntY4mFrF/DMv4nufRuBVecAz/03YOs1i3udYvH11JfIWI7y63Ox+Hq8YObA118CrD4XeNU33V/fjh0wq190XUZZdA4B3Sulw/bwg8DZr/V2oFYbq5IiN+2do23oDZX5qoTQUZn5SoiEIyAppDKFgH8AOHQvBu79GJQTe2RJ0JO/BHQdG+Yfx/6uM/BL7Xwsm34Cs8d2Y01/B8Sh+yvftRUKBIzFLZp1Hbj534Dhx+zux2NFIt5zT12Gk5Z1x1pc2bKsGzuPBQlkb0x2Dctjn88XBMbNS/2bdWRSip1RXMzKvnasdMkp3Vbkfj5zdS+2r+vHXzz7JP+soRVnAQ98HZt65Gd1sLMF3W0ZXHqS3NW/a+8YTlnRg0f/33Ox0XTiFi/6/+a5W9HRkkK7MYspoxXrBjvwzJNKS83Wme5LVTfw6vOKhdkqxw4UZxG6iK+AdBhfe8ZK7BsL0Gk1ANNZ6bLsbA23CRJl7MDTo/LftiGK2IEGp8vMwZxZbNOtgY2FzG0PDo3PYdfwNC7fWnCUlzfcqqvz1TAKC6/x/WZJ71rvnyHVx3IzmSXR9uZLyJcZm5HnG6spZU3pGJBzEgAYeVK6Dr/zGuCh71T+mpbztZLYgRCZrwDsTHSLRw5O4IM/fxyGYWDHwVG0ijwGBgbxJ2azy20xrCpqSCwXYfHmlKIAf/xdYPNz5PflndEtwUadl0KOMJs91VN4BaTr1ty0EwjufM25CTVzY/K6EUp4RW2drxarqtDUs1lQUsCF7yhkEFdK8Xlv9XkF4VUx/96ZjjLna1HF1vTRUidsOYaxMHZgflyeNzsGgZ6VZrRHFjjvLYv7d4TFFl995uEGGix2wOrV4D+u7A0Viq8k4XAEJIklWwvZT//3x8CtHwNOeTGw/HS5Wz6yA0p2Alde9SKcd811AIDup36JM3pmpVt29bkVvrGAsljn68F7gN9/WH49uAmA2VUewIUbB/HBF522mFdvCrYs68bIVBZjM7l6H0pF7Dxa6tp98Vkr8boL10XyXues7ceqvnZ85bpzg5VJvvhzwDX/Ibtrj+9Hy+3/hW+/5QJc/5eXApBRARY97emS19yyrLAg3ba8G//v+VvRJvJ48flb8ZXrngGlbGu4OHf0pGLxudqxAyNPAluuBt7yW1+H4brBDhwen7d3phfDdIXO18CZjyF5YP8JfOceWYoW580ZN6y/w/Sixdf18jrgk7H2BzPu41lbl+Cdl29Cd1t6YTVCdhKAKCw4glCtxfP8eKG5DQBsfFZtHS5EctnfAX/5kF0SXciOC/f3PTGbQ2taQXs9Kl62X1f4emYYOGrmEpoZl4G59WPAbZ+QX1tl1aFjB4K3kreifh45VCoW/fLRI/jyrXsxMpXF4WOymVGqvRdtmRRuf+8V+Oabzw93TKQyimMHiulfB1xrfk70svN58bm0GtnD1WJgg6w0uOMz6MzLcRFkg9USalqdMl8rcpXXQLCyNk4s6tXorJkp/swXC7lWdnjPyoL4+sTPgJv+ufTnx/eXngfnJwvf778T0HJmfr0pws6YucEdQ9Jp27dORnzUuhrG2jzxbeDYWLED9pZ4gEtPIXaA8y2SbDgCksTVHwbe8LPC9y/6DPCyLwFdy+Wiev8d8v615+PC7WfjYX0jrkndjfMzZllHxc7XKmS+7rxe3l773zIDC8DRiXlcuHEQ337rBVja41w6FyfOXtsHALhtd5gmA41DeV7t319zMs5ZW2Fppg/9nS247b1X4Ipty4L9wFmvljvd6y6U4f6H7sOFmwbtz1VbJmXnVva0lTouiku5l/e04eVn9AEAlgwOleTUWqzplxPKk5aWRS6EWDz7kp+TbpMVZwUat2sGOqDpBg6Pz2Emq+JPvnZPxREXlTbciip24CWfuR0/fUhOtJcn4DxRjtUBftFNt8y4F7/ogXv3ncBAZws2LenCe567DY984LkLnzQ/Kd1LoUTPKjlfLderxbZFlkmSylCUkizKMIu4YsZmchjobKlPFun264ChLcDKs+X3e34rb8N2477xA8Bv/j/zZ8flbYQNt05Z0YOz1vThEzftKtmUGTWjnPaNzeL4mDnPMN3pK/vaMVjuYCfRYDlfnSoDupcBr/kBcN0vSu8vfm4jia/WGL/hfbjwwBcBBBvjtvO1XHydG5OO87BYpdq1dL6S8FjZxctPL73/Vd8EzvtTYNW5hd+zFa1VnAmbm5YC/R2fBvbdAXx4DfDjtwNHHwG+erV8zrLT5CZXfq7QtK1zEDj7NcC7HgZe+oXo/n1uWGM251PdaBgNFjsQfN6e0+STWsqjRAhJGI0zgkn09K0Blp0KvPRLwAs/JS80qYzsTjl1TJZbdC4F+jeguy2Du9ouwVnKHjzr+HekY9bKLwqNlfm6iEnPk78C1l8KbH+DXUZ1ZGLednAkgbPX9mOoqxW/eixY05tG4/59J2x3kiLQuAu5gY0LS5emh3GT9iZsF0+it31huZsl6g12tQJZc/Lkktu0bUU3XnvBWnzx9WVO8hCZfb6M7pKvtWRroKevG5CC8L7js7h19yhu2jGMXzx8xOennJnJqmhJK6F3t63pWFjnmxflDptyF3IS6GqVn9dFN92yYmtueB8w/ITr0+7ffwLnrO3zFsOyk+HyXoHqOV8tx0vGXOxsuXpxr0eqgqgwduDETA79HXWIHADk/OmddwMv/5r83hZfxyt/TbvhVsgM2xCVE4oi8E/XnoKRqSz+44YncfueURiGgeNmVc3e0RlMj5sO3FZGDdScvrWyzLrDIaMeAE66cmFJe2fRc8NUFERNUdxZPi3PuQYgHYrf+KPSzvVF5N1KlGfHgPZKxFfr+lHFXP1y5scLrtzz3xbd+8SZwU3A5e+XERvFDGwErvl3KbxbmfEnngZOvhZ4Tpn7dd9twA1/XxBbH/p2QagVCnCyKdZOHi51vtaTTjOmya+pqaE3kvE1VMWK65gmJGFwBCSRM14OnPO6wvfdK4CZEWDf7cDa8+2z6Y6l12DaaMPSyUdkGUbYjCULISCEUfmaeX4SGHkC2HS5fZemGzg2OY8VfckRX1OKwFWnLsPNO4Yxn9fqfTiB2Ts6g0/cuAsPHZzAGy9eD0A24Ek1qhA2sFGG8ueLSpMP3Y9eYxJnKE+hx0F8/emfXYxvvfl8+W+ydq5d3CeZlIIPvfh0hxL4KjXcys0Cd3xKfr30lEA/staMVdg3Nms7qx8+OF7R209nVXRX0HU8itiB4alCLvS7r9xSxVduHqzM18XHDpiL6Kd+B/z6Hwv3z44B/3MtML4fJ2ZyeGpkBues83C077wBePwnIfNegao5XyfMhhvX/Rx40w0sDW0QKs18HpvNYbCrTuIrIA+8d63MIhwxNyXCOOD0snP+/LgUzyrJtAxx/Th7bT9ees4qfO32p/HHX7wLNz0xbDcvu3vvGNoMM3sw7CYJWTxnvQZ42x/C/e7b+4HeNfLrRnK+DhTEV8WMStANQ/Zw2P0b4PEfO/6Yu/P1RGXOV5uIna+9a4C/egJ47r9G9z5xRgjgsr+V8QJOtJvi68xxKeD3r1+4SXHvlxf+nJXD/d4DwLpL5NdjewsRMfWeB/SZufPj+3ye2FixAxZBRhVjBwiRcAQQWcYEA5g4AKy5wL77bddegi93/AkMJQ2c8/rKX9+MHQgatL8AqztlUYni8eksVN3AcodGTHHm3HX9mM1pONwkXYdvfPwYnvvxW/CxG3eiPZPC25+1CWlFYFkjl387lVeP7AAALBXjC2IHAGBpTxsu2mxO3izna0tIx1A1Ygemh4HPXAA8/B3gme8Blm4L9GPLutvQklZwoER8naio+dV0Vg0dOQAUOd+q6HzdYzZ5++abz8dfXnlS1V63meiulvhanLOnFjXqOXgPsPcWYN8d2P3Qbbi+5b14xjKPxcG3XgHkZ8PnrFbL+frk9UDXMmD5GbKLOGkIKo0dqKvz1UJRZMSLRXn2oxdWxmvxz4bNewVQScPGv7/mZFx30XoAwGd+t9uOHfjDrhF0w8x2pvO19qRbK8ucHDI3GDOLbHpUTTqHgBd+EgDQpsnrsWGgkOfpkiFuZb46NtxalPM1YvG1vU8Kh0odMqiTwNbnydvbPibnIX3rZJWAKPp9P/W70p9p6QayE/Jz09oFDG6W9x/fLY1HgLvLvFa0dsm4EZ9Yp0aLHRAh9sTzbhsqhCQMjgAina8WRYvRk5Z14y//7l8h/vapRYaPWw23Kpz0TByUtz2Fju2HzWZbKxpZxIuAvg4p/E3MLbKEOALufXoMV3/8FhyfzuIH9x3EN+/ah/+9cx+W9bTic689B99483nobstgWU+b3W25IbGcGp+5AHjgG/LrIvFVK5+8H7wX+OXfFib1OTMr1SV2wBURfvG8gF2/ljvnf/xd4Ip/CPxjiiKwdqADD+w/gT0jM1g32IHjMzl7nIVhplLx1byt5tpo94hc7Dll7yYFy4W86MxXAPirHcDJLwROFLkzxvcDAD7x41sw9sivcbKyH9vy7rEENkcfCffedmbfItzhU0flGDnz1UAq/GeURIedHRfyHGhlvtad1UXZ2mGcr9PHCl8bhhRjK2koVMHm3VBXKz7wwlPxjy84BffvH7fP98cms0XiK52vTYMlvpY346o357weWHoKWtUpbBP7oet6QSDOO3d3t5yvmWKhRlPl2KrI+VqlygknDj8oM5v33xE+LoSEY/lpwOrzgLvMXNb+DfLc195fyEoupr0fWGVmcveZzvDOIaC1V4qvB++VYmy6AWLQ+taVzq2cMPQixbP+hLluW5mvdL6SpMMRQKQLCADSbdINVM5iJxNCZr5WPOeZkJ3K0VsQX+/bJ90iW5cny5Vh5Y02ovj6pT/sxY6jU3jL/96Lv/7eQ3j/jx7FXU8dxyWbh3D1aSuwfZ2cMH/oJafhL5/dwC5Ey/kKyJyo8QN2F+slGMf0vAocuAf4j60yL+rRHwJ3f94WoQrO17CCXxViB44+IrMsN18Z+kfXDnTgXnNcveJcOUl99FAIEcFkOquiqzW860NUKL54sWd4Gl2taSzraYCJdZ2oWuwAAPSskFEWEweAvCnMm+fn7vwoZo8+Kd/zxOMLfzY3IzPWLK7975BvXoUFx65fA4YGnPmqxb8WqSp2dlyIU2Be0zE5r9bf+QrIRjAWYTJfZ4YLX6tZMzeyL/z7C6Xi68d56+W1+Qrlfvyi5X1oQxZ9KXN8U3xtHpaY4qtfbmQ9aOvF0qnH8avW90LZeT2QMsesNV8qw3K+thYLNXYzugo3J4BonK/ffR1w2yfk16kGOBfFnXPfBGhmpFT/OnnbMSAdxy/7MnDtJwrzi751BaerFcshhMyWHdkh4/bWX1rb43ejf52/87XBYgcKma/+z7WdrxRfScLhCCAF5+uq7UA6gomDUMyGWxXw6A+AXb+RJSXdy+27f/fkMDYt6cSagQYqr6oBjSq+js3kcNMO6eC5f/84uky3XVbVcfaa0ony5VuX4vTVDewOKJ7YH7gL+PhpwDHp0lsqxnHBxgHg6VuA6aOy8ZC1OXDkIXlrZb5W4nxd7MLg6COyqV4FJW9rBzrst3/2yTL8/+CJ8PEWM1mtIuerEsHaaMfRKWxe2lWfTugNQnsmhb6ODHYP+3TRDcrgJgBGIZvM3HRYKk5guSqbtImjDy/8uR/9KfCFZ8mvX/ol2TwxDNVYPI/ukovjoWTm/zYyAuEbbo3PyuvgQGeFefTVZHWx+Fq2aXXwXuAzF5mNEMuYHil8nZs2YwcquT5Wfo47aZm8Vr01/QucquzDP6x6AC/YYuaGMvO1eTjz1cDZrwUueVe9j2QhrT3oypkbDccekdEzgCz7zs0uqISwYweKna+zY/K2ktiBqJyvui5zxNddLL/XGmtuHktOfbEZzSIKguqGy4BNVwCn/xGw/bpCtWb/+oL42reu8BqDm4Gn/yAr1TY0ivi6XlZ6ah4b5YbRUM5X+7odRHy1G241zvETUg8ovhJZqtHaIy9ekSBPz6GzHDUV+P6bgCd/WZKhNJfTcNfeMTxr69LqH2qDYzV7mmwA8XVsJoerP34L3vV/D+AXjxxBXjMw1CUdhtddtB7rzSZOZ63tq+NRVsif3w+89gel93UMYUvnDK46dXlhET15aKH4WnHmq4JFLQwMQy5glp9e0Y+vNTcyutvS2LqsGx0tKRyqQHytOPPVnMRVnA1dhqYbeOTQBM5a01edF2xShBC4aNMgbts9Wp08XcsZfnyPvB2Xn/9l4gTWK6bj6kiZ+Jqfk5toVom1WzMNT6qweB57SpYpMo+v4aik4daJ2RwAoL8RYgd6V0u31Tmvl8KSmis89sTPgOHHgG++fOHCujh2YH4CmDpSWfOXRWzetWXkeDhqyI3H1xq/wDnLFLlR0QjluCQYmXbgRZ8uqRJrGIpEfGV0F5A145mmj8l5/ucukdURJo7NeeZM8bWjEuerFVtTZfF1dlRWU5z6EuDV/wdc/W/VfX2ykEw7cME7ZExexowwe/5/AFd+oPAca57SX+R8tWIHgMJ9QOM4X/vWyc/S+L7SKqFiDL2hMl9t00SAeVle0yEEGrfZMiE1onFGMKkfqTTw9tuj2y0XZuZr2DlPcdfHojD0B/afQE7VcelJyetS3UjO17ueOo4dR6fw4wcP4z9ueBIdLSm8bPsqAMAztyzB889YgWU9rc2Ztzm4Cdh4udyQeNmXgb/dC5z3VihzY3JRXSK+mpnET/0O+OGfAte/R34f1vm62NiB8X2yC2yF4us6Uyw/yXSKruxrtxu7HTwxi0/etAt5TcfYTK7k5w6emMXTo3LRpOsGxmZy6GmrpOGWvK1Ww60nj05hNqfhzDUN7LKuERdvHsKRiXl86BdPYGJ2kecOa1EzuhO46Z+BQ/cCANaLY1ghxjCX6pKfxcMPFH7m6dtKm3RVIr5Ww/k69lRprAhpGCr581rnooaIHQCkm9uKbip2vx7fLW9P7F1YVlocO/D0rbK02urGHYbFZIaPH8A/pL+B5cJs/jW2B9h5AyMHSPUocnOLsV2FCqHpY8DO682vC2Oh6s5X+wSzyGinYtRcoSFw93LZDKoRhe848qy/A970K/fHO4eAqz8MnPMG2Qyxc6nMirU45UXAqS8F3vAzoKtBjDyrtkth9ZPnAP91sqyYePBbZU9qrNgB61CCmCZymoFMSkl0JRohAMCOE0RSvCNYdURlsQPFJXpFQuwTR+WO+WmrkieqtKZTaMsoDSG+PnhwHC0pBZ2tKZyYzeP8DQN4zXmyrOectX04e20f3nbZpubd5VRSwBt+Wvjeir24+UMFl+vxPYVuqYfutYUoADJDOQxCWZywZJXtOeU2B6AgvkrH7qq+dhwan8NsTsUlH7kZALDj2BR+8fAR/OFvL7cjP973w0cwMZfHT//sEjx4cBwTc3k8Y30lZYGSakivn/ndbvz7r2T+6FlrKnDJxIxLN8tGFF++dS/WDXbg9Reur/zFOgaAruVyUTAqf8eaIbBESLHp/vVvxcWj3wO+8TLgXY/Krta7bih9jeImj6Gp8BOi68DYXlmaSBqOSjKfrdgBa1OyIbBEpvkJoMtsAHPsUVlhNDMiKyWGilxXRYITHvshAAFsfnYFb7yIzbvHfoQ3p3+JvJFCbv0VaDlyn9xc2fycyl6PkHKKhHxlbA/QbfaaKP78z4zYDU9zmg4BHS3FRQq287WOsQNHH5WuxMMPAL/718K/a1HXNBIJF7y98PV7yiJflm4DXv7V2h6PH8tPA174KeAn75Dff8m8Dmx7fuG60qCxA0HWLnlNZ94rIaDzldQCK/M17JxndGfh663Pt7/ccWQSQ12tdol70uhtzzSG+Lp/HCev7MEzt8gF5plr+rB2sAPve97JSKcUZFIKutsaaFG8WCzx9bZPALr5+z9wl7y96M+By94rsywtwk6QxCKdr0cfkQKulXUVktX9HRjqasH5G+XCZlW/FF//7+4D9nN+8bDM9PzYb3bid08O43O/34Odx6awZ3gahmHghkePIq0IPPvkZaHfX1Gs7KjFy683Pl4o5bXiL5LM2sEOfOF1shv76FR28S+44kxbeAWA8c4N9tf5dZcCz/t3YPa4XKBmp4GHvgOcfC2gZICOoUKpYBgW63ydOgKoc3S+NiiVZD5b8TuNJb72yduDd0vBf35Sul23Pk/eP3Gg9PnDTxTKSJ/6ncyOrURcWkxm+NhTAICM0NAytAE49zq5wfLCsE3xCHGh2PmanwVGzOvH1JHCc4qE2Kyq4zOZT2DFr4sEtKo4Xxc5v7jlo8DP3wXs/o38Pjspbym+kmpw9muAv9ldel9xLjiMBo0d8Cev6cx7JQR0vpJaIMzM17A7zsd3SbfI224r6f77xNFJnLwiZJ5mjGgE8dXK0/yj7atxyooe/OTBwzijkZtoVYPijChAOlutctItzwPWXyyzLStmEWWjgBRfB0+STsMKaMukcM/7r7S/X9XXjrGZHL59936ctLQLe0am7dKinz50GD984FDJz49O53DTjmFcuGmwIjHE9qVUwfralpEO8c+9djtLnEyuOnU5BjtbMFoWG1ERK84Adt2AUaMHj5z7r7h8pQ787C8wavSgf/3ZwKC5iXDgLmDkCSA7AVz0F8DY04twbSzCuaTmgHvMjRGKrw1JJZnP1nWwt6ORxFfzOvjjt8u81E7T/XrSVcD9Xy/E1ADAiX3AkQeBM14FPPx/8r4KKxcWdf04sbfwddcy4LK/BS5/P/NeSfUwM19VQ0Fa6As3IYCSCA4tN4/LlQfRujcFqFn5WZwbA5Q00FrJ/L9Kztepo8DM6MLKpkYpXSfNT+eQvI5Y0TXTxwrVEkZjxQ5Y82s9wIVbiq+NIxwTUi84CkgNEBBCr8D5ukt2pe5eZi8CVE3HzmPTOHlFcrPIetszmJzz6IZZA367YxizOQ3nrh/A889YgT+9bCOu2BbzyefgJuB9B4G/2SWFpNNeVnjMiu3ItFf++ottCHHk4YrzXu1DEMKeTK3qk/+WXcPTeOUz1tgNubpa01AdJlo7jk5iz8g0tq+rrMxfhNhB92NsJodLT1qSyKZ8Xgx2tWBsuhri65kAgIf0TTjrilcCG54Jo3cNnr7qyzhjTR/QOSg3Ag7eAzx5PTC0FVj9DOCqfwau/KfK3nMxzqWnfgfc+l/A0lOBlWdV9v4kUgrjP/jfd2IuD0UAXS0N5CMocvjhyEPAL98jM+vXXyLdccXi6+M/kbdn/XHhvkozIxcTWzNWLL4ulX8MCq+kmpjjYpexqnDfyrNLn/PoD4Gb/xUA0DP2CNpEHkKbBw7cLR+fHZOu10o28KrlfJ06AmhZGT0wtLVwf6qBNoBIcyOEnD9ZFDdlbLjYAUmQUZVVKb4SAlB8JbVAiPD7dLoOHHscWFKY3Ny9dwxfunUvcqqOU1cmW3ytp/N1Pq/hozfswIahTjzvtOXobsvgfc87GR2NtACOitZuuTi96oOFMrOBjUBP0YLinXcDb/5t+NdezOJgdgyYPCgdiVXipGWyYdiK3ja87JzVduM0t0Z3v37sGAwDOKXCjRHFynysgvp6fCaHwUbogN5gDHS24PhMNWIHzgIAHOk8WXaaH9gA8e5Hce7FVxWcxmvOB/bdDuy7Q7rChZB5q5uvdH9dTxbhXJo0Ba/XfA9oZwZwI1LJ6W9iLo+e9owdWdIQ9K+XLldAOl1Hdsgcv/Z+KayO7y88d9/tUsBZdlrhvorF1wpja9RcqQuxK3xkDCG+tErx9TGjEFGDFWfJzezX/1TGdTz9B+D3HwEO3Yclx+8BABhCAfbeIp8/N1Zh3itQFeerYRSEMHUO2PDMyl+LEC+GthS+Ls5FRmOJr2Hm7XnNKG2gR0hC4Sgg0WNnvoZpY/yULFU1d8Z/+cgRvOLzd+DD1+/ApScN4erTlkd0sI1PTx3FV8Mw8I5v3o9dw9N4/zUnJ3sXc/OV0kn3mu/L5lwWS7YCq7dX8IKLWBwcuk/emqJYNTh1ZS9+/55n4ba/uwL9nS3YtNQSX5eUPE8Rci74q8eOAkDFrnTrX68vUn01DAMnZnIYoPi6gMGuVhyvgvM127US79D+Gke2vcH9SVueKzu352eAtRcu+j0XtTkxeQSAoLDUwFhbtGHmCeNzefQ1Ut4rIPOMX/M9+ZmfG5OO1E2Xy8d6V5c6X8eeAoZOAlq7CvcVb+SFosLYgYkDUrRNmedLjhESBabz9ZAxBL3N3ABr7ZKb2RsvKy3bv/NzWD5+P57Q18BYeqrMDgeA2ROV5b0Ci68sAmQZuDpf+J4RNiQqlhSLr8XOVx2NFDtgHUqQeXteZeYrIQDFV1IThBRfw/zI4fvl7cpzMDWfx3t/8DDOXNOHb775fHzx9eeiNZ3y/vkYI2MH6iO+7hmZwW93DOOvn7MFV56S8EXauguBd9wu4wiqgb04qMC9tO82mYW2+hnVORaTdYOdtqvsWVuX4Kw1fQucrxuXdGFlbztGprLobk1jdX+F0QtVih2YnFeh6gbFVweGOltwvAqZr0+PzuKX+e3Ysn6N+5O2FZokVkV8XczmxNQRubhPJcCd36RUEjsyMZdvrGZbxVjCzNCWQhxN3xqZr/qTdwLHHpNfD2wsLfFflPO1grFhNtvC2gvkLbMrSRSYma8jRi/0DnMDt6Uou7U4sumJn2Hp5GN4QN8M0b1MNm8EFud8rUbsQLEIBshj+ZMbgXfcVflrEuLE9uuAV3wd6F5Z6nxttNiBEIfCzFdCJBwFJHoEoMAIN+c5dD+QbgeWbMMP7z+EyXkV//zCU3Hx5iG0ZZIrvAJSfJ3KqtDCdCapEnc8JSfBLzhjZc3fO/YspuPUvtuBledU3GwrCBdtGsKP33kxVvW1I2UKsv907Sn40uvPxfkb5YJo/VBnxQ2ulCplso2Z4iLF14UMdrViYi6PnFqBwF/EnpFpALCjKBxRUsAffRU4/eWFTOTFsJjPx9QRdqNucCqJHbFiBxqSfrO8ujhSYPNzZLXEYz8BPnsRoOUWuud6Kry2CgUVbUyM7pS3z3wPsP2Nlb8/IV4MbsajG/8EN2jnQm8xrxvFjm+ro/vZrwXUObRpU3hcbIboGCwSX08sIjamCrEDU0dKv2/vB9Y8A1i6rfLXJMSJ9n7glBfKzbAS0b+xGm6FuW7nNJ2xA4SA4iupCcIsiAsx6Tl8v2zqkkrjm3ftw5mre3Hmmr6oDrCp6O+QotJYNbqWh2DPyDS+f+8BrOxtw7rB6ES+xGI5X8MuDnKzcrNi3UVVPyQnFEVgabd0ap26shfrhzrxkZedgY+/8iz8y0tO8/lpdwqxA4s7Poqv7li/kxOzizt37BmW4uvGJZ3eTzztpcDLvrSo9yqwGOfrUYpKDU4lsSOTDe18NcXX4iaIGy6V1RIv+WzR88rE14ob91SY+TrypCzl3vBM4NqPl0boEFItlBQe2fYujKAfhuV4bSkSX+fH5e35b7PvekI5STarmx2Twuv0scU5w4HFbe5OlTlfK41AICQoXcsWxg6IxpFuwly36XwlRMJRQKLHznwN+HxNlZ3bV52Dyfk8dh6bxtWn0bVkYXWhPzQ+V7P3NAwDL/n0bXjo4AQu2DRYsbuReGEtDkIuoB/8JqDngS1XV/+QXFjW02beShE2k1Lw4rNX4YzVfRW/prB30KvjfB3sZLfucoa6pPhaSe6rrhuYy2kA5EbMqr722jbZW1Tm62GgO7k54c1ApQ23GlZ8XXGWjIJZf8nCx9ZfWvi6WrmRlcYOjO4saWxKSFTYQo0luhZHDbz6/4BzXi+d4ktPQU604kBqrRQ4c1PArhvl3GjDZYs8isXEDhwt/Z7NG0nUdC0FZkYK3+tqQ22QhYkLymsGWii+EgIGoJHoESEzX0eekJ1EV56Dp0dnAACb/BxWCWL1gJywHjwxi7Nq4AbWdANHJ+cxOa9i3WAH/vyKkyJ/z0RSifqga8CtH5eZmlZmXw1YboqvS7vbqvaaSohJnBdjM1kAQH9ng4oydWSwSwrS9zw9hlNWhmuM9uov3om79o7hXVeehD0jM/6u16pTofNVzcqswG46XxsZe/Ml4PMNw2hs8XVoM/DeA85RMO19ha+tBluXvBtoWcyYqnBDdORJ4ORrF/G+hATDKlHWLedrfrbw4MbL5H8AcME78Ic77oIy0VLIeH3ke0Brb+W59lVxvh4FMh1yUyU7WXn+LCFB6V4hna9aXlZFTB2rXp+JKlBolOn/3Lymo6eNshMhHAWkBpjia9BJzyGz2daqc7D3gBRfNwxRfLVY3S8XcwdPRO98ffDAOF79hTvtJkofevFp/FtERSWxA1NHgcmDwKXvrmkI/6alnVh5sA3tLdXbgbcmcZXGDhiGASEExmZkMzo6Xxey0nTN/9NPH8PW5d24YONgoJ8zDAMPHhgHAHz3ngOYmMvj5edWIcc1DJUunq2cPjpfG5rCnzfY33cmp0HTjcYVXwHvDO5XflN2cVfM8/6VH1jcewkl/NiYGZUbE3S+klpgjvHc4DZ0AkBbn/Pzznkdfr7rdGRmxmTsAADsugHY9oJFNE2sQubrkYeAJdtkBm12Cmjrrfy1CAnCwAbp+B7fL0XXyUMyvqZBKDhf/cdVTmXsACEAYwdILbCcr0HnPIfuk5OagY14amQGQgBrmTFq09WaRn9HBgdPzPo/eRHouoE/+9b9mMtr2GVnPHo02CGLpILYgeykvK1x9tifX3ESfvJnDuW0iyGk+FLMzU8O46x//g2GJ+fxq0ePYKCzparCcFxY1deOz712OwDgcIjYkqmsiqyqY9vybhyemMdMTsNlW5dEdZguVLh4njgkb3sYXdPIhO03OG7mFje0+OrFyS8Anv2P1Xs9UUHmq9Vsa4jiK4key/k6fdZbgFd/BzjlRa7Pzam6LFHuKNogXHlW5W9ubW5X4nydnwQO3C3XJmsvkI7Xtt6GKv8mMcWKpRl7Sn4Os5OFaokGIMyeeF7TkWHDLUIovpIaIBTZcCvonGf4CWD5GYAQ2Ds6g9X97WhNc5JTzOr+DhwYi9b5euvuURw8MYfzNkhhry2jYEVP9crMSRmVLA7mTfG1LVwJ+WJpy6SwpLu6zlJlEcbdRw9OYGIuj/d8/2E8dHAC//qS0/1/KKFY43lyLh/4Z4Yn5wEArzl/LVrSCp61dQmetaXG4mulztfju+Tt4ObqHg+pKnbX5IDi+uScCqCJxddICDk2TuyTt1ZzMEIixM58hQC2Xu1ZrZNVdbSkU6Wl/YvZJBAVbG5b3PA+4MvPAdR5YM35crObkQOkFgyYEQPH98jseqDypnMRUIgdCNJwi5mvhACMHSA1wcp8DbgwmJ+wy+D2js5gwxDdluWs7m/HzmNTkb7H9+87iP6ODN5/zcl40advw4ahLiiLUciIN5UsDuYn5G1r85e/WZmPYbqdWwxPyZzX3+8cwcYlnbj6NJaYu9FtZm5NzquBf+bYpPz9bl7ajR+94yKsGeioQ9O9Ct9vdBeQbgN611b3cEhVsT5OQWNHZnLy89vFDDlJJQ23Jg/K2x7mIZPoUULsL+c1HS0pUep8XVQ8xiJiB/bcXPh6zfnyelLcBImQqOgcAlq6pfN1yNxAbiDnqxLW+ZriGpIQzlpJ9AgBJUzsQG4aaO3GTx48hMcOT+Ctz2yccPFGYXV/O367Y9jOuYyC+/efwMWbh3Daql70tKVx0lKK4NFSweLAih2IQfZY2LLjYoan5u2vT1/V/L+LKMmkFHS2pDARwvl6zHS+LutprV/0SKXO19GdwOBJhZU/aUhs52tQ8TUrxdeOFk5jAZiVExVEcnQMlXadJyQiCrnu/p9TTTeQTimlkUpWCXZFb17h9WP8gMzZ3Hi5zHvtWcEIG1I7hJCVCcd3AWNms+PexhFfC6YJ/+dK8ZXzMEI4ayU1QCB4MSGA7DSMlk78888ex5lr+vDnV7BctJzV/R3IqjpGp3NVL/8GgMn5PA6emMOrz1uLlCLwtTedhyVdbGAUKRXFDpjO1xrHDkRBIbg/PJbzFaD4GoSe9kyo2AHL+bq0rrEjITcndB2463PA07cCW66O7KhIdQnqfJ/NaQCAzlZGEkkqyHydONhQC3kSb8Jc41VdR0oRQLqlcGdqMREjFWxu77sd+Par5dfP+wgb05H6MLABePwnwJ7fyu+7G0f8L4wqNtwiJCgcBSR6hBK84ZZhALkpzKIdx2dyuPaMlehs5R5BOav7pVMlqqZbTx6VkQYnr+gGAJyzth9rBtj0LFIqcWZYztfW5hdflcXEDkwWxNfTKL760tueCeV8HZ6aR1drGl31PBeHHR/Dj8msvvwsMHRSdMdFqkLYAg7L+dpJ56ukotiBQ0BP4+QHkngjbHe7/+dU1QykqxlzVcn8avdNQHYKuPYTFF5J/TjjVcBJzy18v6hNiOoSZljlNB0tbLhFCJ2vpAYIEdz7mp8DDB3DWXlx2WaKf6SU1f1SCD14Yg5nr+2v2usahgFVN7DjiBT1ti1vflGveajAmTE/ASjpWJWNhtUPDMPAyFQWK3vbMJVVcepKfmb96GnLYHI+TMOtLJb2NIrzPeAHxOrkDgBDW6I5FFI1lBDCDADM5aXztaOFzlcAFcYOHATWXxLJ4RBSTph8SFU30GG55N52WxWilSqYX43sAAY3AduvW+R7E7IItl0j/7v3q8Ds8XofTQlhNlTymsHMV0JA8ZXUBAEFerA5T24aAHB4Tn40Kf45s8p2vs5V9XX/+6bd+PhNO/HsbcvQ05bGit56lhknjEqcGfOTclFS8+ZH1afSf8L4bB45TcebLtmA15y/Du0UY3zpaU/j8Pi8/xNNjk3OY2kE8SahCDs+RncBEMB1vwDWXhDZYZHqYHdCD5z5aomvnMZKQsYOzE/KyokG6pxN4k0h89X/uZpe5HxdfloV3ryCWKeRHcDSkxf/3oRUg3PfWO8jcEQI/+W9phvQdIOxA4SAsQOkFlg7Y0Gem5Xl7vumFSzpbsVAZ4vPDySTrtY0+jsyVY8d+PnDh2EYwI1PHMPzz1hRh47mCcYWlwIuoH/wFuDBb8UicgAI73yzsPJel/W0UXgNSE+I2IGxmRwePjTRABthIZ1Lo7uAvjXA+osBhZ+LRkeEbLg1m1MhBNCW4TQWQPjYgclD8raBOmeTeGM7XwOcw/OamflaLcJu3uXnZYf5JRRfCfFCEcJ3WOU1ua5h7AAhdL6SWiCEmfkaJBRGOl/3TgpsW87IAS/WDHTgQJWdr91t8pTwritPwp9dzkZntSWEuKTrwCPflV/HoNkWEN75ZjE8JR2cy+raDKq5CBo78F+/fhL//dvdAIA/Pn9t1IflTdjF8/FdwCCzXpuFMMIMIJ2vnS1pbhDayHCnwDx9q7yls4/UCGuo6gH2l0ucr9V5d/M2xPXD0Jn1SogPAv69Gmzxlc5XQuh8JbXAFF+DPDUrxddDsym7qRRxZnV/e9WdryPTWbz4rJV415VbkOZFsraEEZfUopLxRWehNQZhnW8WVrOtupfFNxE97RlMZ1XoLkr3wROzePjgOL51934AwDO3LMGWZfXeDAuxeDYMYHQ3s16bCCGClyQDwFxeZd5rMUIJd/J86NvA0lOBpadEd0yEFGFf4wOcwzXdqO4cNMz8KjsN/Pyv5NcrzqzeMRASQ4LEDuQ1+YzqbqgQ0pxQXSHRIwQUGMHWBbkZAMCR+TSWdFFM8WLTki48PTqDr9y6tyqvZxgGhiezWEIRq06EEJfyRY7n2MQOyNugzjcLK3agcRpCNT697RkYBnDNf/8BDx0YX/D4v//qSbzpa/dgck7FdRetxxdet732B1lOmMXz7HEgPwP0r4/0kEgEBBQQZ7IaOltZvGUTJnbgxNPAofuAM18Vi7xw0hzYM5wgUxxdr5/zde8twMG7gas/AgyxeoIQL0SA2AHVdL5mGDtACMVXUgtkOVygZUFOZr5OGW0UAX14yzM34vwNg/j3G3aEzsl0YnJeRVbVsbSb5dt1IYy4lC9yPOerGz1RL8I63yyOTc6jqzXNxjsh6DHjRXYcncLLP38HxmdzJY/vG5vF6HQOOU3H1uXdaMs0gsOwgs2Jls7IjoZUHyWAg8ZiNkfnaykhYgdOPC1vV50T1cEQsgAlRHWLphlVznw1b8NUFm28rHrvT0hMEfDv1ZCzxFeFshMhHAUkeoQS6OQMwI4dmDHaKb760NOWwbNPXor5vB64eY4XI6aDkL/3ehFCXCqOHZgejuRo6kbIjYSRqSwjB0JSLFTnVB1PHJkqefxQUZzJusGOmh2XJ6FiOeS5DGluJDUTQgjf7DiLmaxG8bWYMM7XmVF527kkuuMhpAw78zXA51TVDWRSdXK+2tcPzisI8SNI7IBqxQ5UdUwT0pxQfCXRI0JkvpoNt2bQhiV0YPqysk/m4h4en/d5pj9W4yIKWXWiUuervnjhvVEI43yzGJ6aZ+RASJb3yt/XXzxbllQeGCt8nuZyGkanC07YDUON4h6tYHOCi+emQm7SBnuudL7S7W4jQjhfrQ07iq+khtjO1wDPVfVqO1/N5W4g260pvqZ4/SDEDwHha65SzS577CVCCMVXUhNM8TWM8xVtFAEDsLxXCtRHJxdfek7na52xFgdhyqrXXgi8/H8iO6RaE8b5ZjE8lWVURki2rxvA7e+9An9+xWakFIH9Y7O4fc8ovnvvARwaLwixbRkFyxrld0vna+xRhAgRO6Chs5XO1wJCdmcPwswIIFJAW1+kR0RICWGcr5qOdDVLlO3rR4AxwusHIYFRAhRd5FT5hBY6XwkBbQMkeizna6CGW1PIK63QkMIQG275srK3Os7X+byGXz92DAAoZNWNEIsDS3x99j8BS7dFd0g1JozzDSg0ieNGTXgs1/yK3jZ86ubd+NTNuwEA775yCwDpeB3sbIHSMN1p6XyNPSKYMANI8ZXO1yJCxQ6MSNcr8/dIDQmV+aob9Wu4xdgBQgIjTRPez7Gdr7zmEELxldQAoUAJKr5mp5FVOtDdmkY789x8WdLdipQicHRiceLrl2/di188cgSdLSn0tPO0UBdCxQ6Y4mumPbrjqQNhnG8AMJVVMZfXGDuwCNYOdODgiTkMdLZgaj6Pj924EwDwtTc+A4ONtAEWZnxoXDw3IwIIXDk/k1PRyTlCESFiB2ZGGTlAak6h51WwzNdUNV1yFVVO8PpBiB9BWmrnmflKiA23IEgNsHa7Azj6ctOYE2y2FZSUIrCsuxWHJxYXO/D4kUkAwHffdqHddZ7UmjDd3M3S8EyDNEOqFiGcbwAwPCkXSXRrV87yHvm7e/7pK/DGizfY96/p70BXayNtxNC5FHdCxQ5kNXQ01OezzgglpPN1KNrjIaSMsJmvdXO+alk5nhSeXwjxI0jRharJ9X+Gma+E0PlKakCYHefsNKaNdkYOhGBFX/uina97hqdxxbalOHVlb5WOioQmlDPD/Htn4iU6hnG+AUVN4uh8rZiJOdmw7dz1/bjm9BXYMNQJVTcaKG7AxB4fAZ5rxw7Ea3zEHSEA3a9+EUBe05HTdDpfixFhMl+HgYGN0R4PIWVYp3C/MW4Yhhk7EEXma8D5Vaq18DOEEFeE8G+4ZTlfKb4SQvGV1ARrtzvApCc3jRm0svQ9BCt623DfvhPQKxRMNN3A3tEZXHoSnTD1JcTfzo4diJfzVYhQ2it2D8sGfesHO6M5oATwV1dtgW4YeM4py5BJKXj1eWvrfUgu0Pkad4IWzs/mNABAOzNfi2DsAGlsgp7BNVOcrWvmK68dhAQiyLw9b2W+MnaAEMYOkBpgdXEPsi7Iz2LWaEVbho6WoDznlGU4MjGPm3YMV/Tzh8fnkFV1bFrSVeUjI6EIlflqxg7EzNmnCBHI+Wbx4IFxLOluxYreeP0easmpK3vx1Tee1/jNiypxhsdsfMQdRYhAf97ZnAoAdL4WE7ThVm5GXj+6KL6S2mJFWvlFC6nmHKC6ma/WOoTiKyHVJMh1W7Wcr2y4RQjFV1IDhHUTJPN1FjN6Kzq4qArM809fgVV97fjqbXsr+vndI9I9uJHia50Jk/lqxQ7Eq+FWCO8WAOChA+M4c3Ufc4oTQSXOV4qvTUXAzOc52/nKeYKNUBBobMyMyNsOVrqQ2iICnsIt8bWqQo29eRdgHULxlZDACATYULEyX9OcqxNC8ZXUAKvhVjBH37TRgnY6XwOTTim4aNMgnhqZqejn73v6BABg0xKWbteVsM7XVCugxGuciIDONwCYnM9jz8gMzlrDnOJEUInzNdUS3fGQqhN0Wcb8OCcCZr7Ojcvb9r4oD4aQBQRtuKWZ4ztVz4ZbKYqvhAQhSOxAzhRfq5rjTEiTwlFAoiekqDStt6CNjpZQDHa14vhMNpjAXcTYTA5fu/1pXHXKMgyyyVmDEGSczMWu2RZgTeKCfYafPDoFADh1FcXXRBDUNgUAak7e0vnaVCiKf+MOQDbcAqqdCdnkBA3Mzk7K29aeSA+HkHLshlt+zXmiyIcM1bAxy2sHIQEJYpqwYweY+UoIxVdSA+ysJX9XhpGT4iudr+EY6mpBXjMwOaeG+rlP37wbszkV73nu1oiOjAQmlLNvLnbNtgAzdiDg/sF0Vn7W+9oz0R0QaTyCOl9FCkg1eI4tKUGWL/o/zy5LpvO1iIChLfOm+NpG8ZXUFiXgFKfQcKua45sNtwiJAjlv98txtjZUeM0mhKOA1ICAkx7DkA230ErxNSRLuuVEcWQ6G/hnDozN4ut37MPLzlmNk5Z1R3VoJDBhMl/nYpf3Clg76MHU12xe5j62pnmuSAxBcy3VeTqXmhAhRCDnu+18pYumgFCCxQ7Q+UrqRriGW1V1tofa3Kb4SkhQgvR6zNH5SogNxVcSPVbOk29dwjwEDMwbbLgVlsFOOVE8HlB8ncmqeMv/3ouWtIJ3P2dLlIdGghIqnmMOSMdPfFUCVs4CwHxeCg1tGV7GkkPAXEsunpsSJcAiDiiOHeDYtwlaNmA7XxnXQmqLErDy32rOU9fMV14/CAmEEmDT1G64xWs2IRRfSS0Q5v/9tsZmAQCzaEUbna+hGOqWjWVGp3OBnv/7nSPYcXQK//mKM7GyL34iXnNC56sQIlC3cwDIqqbzleeK5BDEYgHQ+dq0iGCxA6aLpoWdk4sIGDtA5yupEyKgEcN2vkaS+Rrw+sGGW4QEIkhckHXNZrUKIRRfSS2wJ1w+jqX8DAApvrbT+RoK2/k6E8z5evCEFLov3DQY2TGRkIR1vsZRfEXwzFfb+ZrmZSw5BBSY1CyQbon8aEh1kadA/7+vnR9HF00BoQR0vk7IjQmOD1Jj6pr5as+vWDlBSDUJ0nDLaqLHnHZCKL6SWmA23PLd78rPAQDmDTbcCstAZwsUAYxOBRNfD52YQ3dbGj1tbFbUOIRpCBFT8VX4+uNtLOcrXfIJIqjzVWO36mYkeOwAXTQLEAEjObKTdL2SuiDszFfv5+XrHTtA8ZWQwAgB39iBvMommYRYcBSQGhBwuztX5HyloBKKlCIw0NmC0ZkcvnLrXvz84cOezz80Po9VjBtoLOh8NbW1YPKr5XxtpfM1QYRxvnLx3GwIBIsdUTUu5BYScGzMTwJtFF9J7SlMcbw/p5bztarNedhwi5BICLInruo6hKj2hgohzUm63gdAEoAdO6B5Py9vZb62MXagAgY7W/H06Ay+f+9BbF7ahRecsdLxeaqm49D4HMXXhiNM5utsLBtuhYkdyKoa0opAmgJMcmDma6wJ/Oe1Ywe4kLMJ+suj85XUCUv/9M2HNJ9Q14ZbzHwlJBACwndDJa8ZbLZFiAlHAqkBAVucmrEDcwYzXytheW8bbt9zHDlNx46jk5iczy94zgP7T+DUf7oBTxyZxKr++Il3TU0o5+t8LJ2vSoDsKIv5vE7Xa+Kg8zXOKAFjR3Iq8+MWIBTQ+UoaGUUEE0Dt5jyRZL7y+kFINZGxA97kNb26TnZCmhjOXEn0mJmvvnlkZuzAHJj5WgnvvHyz/bVuAA/sHy953DAM/MsvnkDWXLiupPO1wQjjfJ0DMh2RHk09EAKByo4BYD6vMe81aYRxvtK51JQEih2Ioht608PMV9LYBHe+MvOVkGYhiGlC1XRWqRFiwpFAoseOHfBL2bdiB5j5WgnnbRjAJ199Nj756rORUgTufXqs5PEdR6dw774T9ve97Wy21VCEcr7OApn4lVUH9DUCALIqna/JI+BinIvnpkQENTZrdL4uIHDswBSdr6QuKPZawPt50WS+WiYQvzdXAUNjbA0hARHw3zTN6wadr4SYcOZKaoZvQaHlfDXa0MbYgYq49syVuPbMlTh1ZQ/uWSC+TgIA/usVZ6K/I4NLNg/V4xCJKwGdGVpeLg5iGDsgQsUO0PmaOAI7X7NcPDchQWMH8lbDLWbIFRGi4VZrb+RHQ0g51gzHT6ixYgeq6ny1N7d93OFaVt5y846QYASIHVA1vboxIoQ0MWy4RaInqKPPynxl7MCiOXfdAL519z7kVB0tpjtwx9EpZFIC1565Ei89Z3Wdj5AswB4nPs8zHeJxjR3wdcibZFUdrTxPJIwwma8UX5uNoLEjdsMtOmkKCMV/aGgqkJ+h85XUBWE5X32eZ8eKVFWsCbi5rZriK2NrCAmEEiD0Na8ZyKR5vSYEoPOV1AKr3Mf37CxFJTXVxnLCRfKM9f2Yz+t47PAEsqqG137pLnzl1r3YtKSLv9uGJeDiwNykiKO4FCS432I+rzF2IGmEyXylc6npCNpwz3K+UnwtQgTIfM3K6hdmvpJ6UPBheA9yLYrNlaAmEHVe3vL6QUggAsUOaDorVQgxofOV1ICAk57cDPKiBS0ZZpEulu3r+wEAdzx1HHN5DbfuHgUAbFnWXc/DIl6EdIjH0vkKEcr52pbhZC5Z0PkaZ4Is4oBCWTIXc8UEGBtW1URL/K4dpPEJmvlqb65E0nDLB5WxA4SEIcieuKoZ3CwlxITiK4keS1SCjysjP4e80oZ2haXEi2Vpdxu2r+vHf9+0C2ev6bfv72nnkG9cQjpfY5j5qoRwvmbzGvo6WiI9HtJgCIRwvvKz0XQEHP95TYciAKWq4kyTE2gFbAlL3JggtSdo5qvVcCuazNegY4TiKyFBkFntPjnOus6qS0JMOBJIDQjq6JtFVrShnc22qsLnXrsdy3racMdTx7F2oAN/ccVmvP1Zm+t9WMQNW3tNrvgqhIAeuOEWna/JI4C7T9cBPU+BqQkJkh0HAHldR5oLuVJEgLGh5eRtihsTpPYEdb5ama/VFWuCNjRl5ishYfGbt+c0g9dsQkw4Ekj0BM18zc1gXrSx2VaVWNLdis+85hwAwCvOXY2/umorVvXFT7CLDUHHiRpj8RVhGm5paE3zXJEogrj77MUzBaZmI0zsQIau1zICZL4yz5LUEct86u98lZ/j+jpfuXlHSBBEgKx2VdN5zSbEhDXIJHqCTnq0HHJIo43ia9U4dWUv7v2HK9HXzhzdxscaJ/7xHACAdAzF11ANt+h8TR4B3H0sG21aAvdT03Rk2GyvlECxA6bzlWOD1AF7KeDzvEgyX0XA+ZW9QcHNO0KCIIepT+wAM18JseHsldSAoOU+eahIoYWLqqoy1NXKco9mIHDDLbNpShydryJMwy2NGzVJI5DzNS9v6XxtOoJkxwFAXjeQZrOtMoLEDrCkmtQPYccOBMt8re68NWimvim+xrChKSFRIESQ2AFmvhJiwZFAoseccAm/HWc9DxVpZLg7RhJJ2MVBDMVXBHO+AdL52sqNmoTBXMu4EyTzWdV0zhPKEUoAVx+dr6R+KEEr/+vZcCvGm9uERIGAv2mCDbcIKcCRQKJHBPyYaSryRoonaJJMuDiQzrcA4othGJin8zV5MPM11gTJjgNkWTJLGMvg2CANjjA3mP02WFRNbiJUNXYg8OZ2fDP1CYkCJUBcmKoZVR7PhDQvVLlIDQgoKul55JFiOSFJKFwcyPKlAGXHmgHDAJ2viSOI89WKHWDOdbMRJDsOAPKajgznCWUEyUNmwy1SP2znq18+pB07UE/nK2MHCAmEEL4bKnnGDhBiw5FAosfOefKLHVChQmE5IUkmgbvxWuJrPBcHQVIH5lUNAOh8TRqB3H0srW5WgmTHAWze4YhQ2HCLNDbmkPUb43bma1U3WAJubqvxjXUiJApkXJj3uMprBtf2hJhQfCU1IKCopOWhGmk2hyIJJYzzVcSydDRo7EA2Lzdy6HxNGsx8jTNBsuMAmR/HCpkyBBtukcZGCbjBbMUOVDd1QAn03nS+EhIOEWCcqprOtT0hJhwJJHpEQFFJV5GDggxzYUgSCVwWNycXBkFmPE2GNDb6iy/zeel8baXzNVkEcb5a7j7GDjQdQbLjANNFw42XMgJcP+h8JXXEmrH4Zr7q0iUnqjnHsedXPhV4+TlApHj9ICQgQUwTeZ3OV0IsOHsl0RNUVNLybLhFEkwI52tMS+JEQPElq8oFFGMHkgadr7EmQHYcYHZO5iZtKUHmWWy4ReqIYkeQeQ9yTTeQqvr4DjO/ouuVkKAI+PdqUJn5SogNRwKpAXLSo8A/8zVvKMxyI8kklPM1puJrwLJj2/lK91uyCKLO2w236O5rNoJkxwHS+cp5QhlWWbXXAGHDLVJHrCmOf3Meo/qxImEabsV0fkVIFAQpSIpkTBPSpHAkkOixd7t9nqeryNH5ShJL0IYQ8RVflYANd/JmJlwLxdeEEcb5yrLRZiOo2Y2dk50IUFat0hVO6ocVI+C7f6brEWyuBHW+zsd2fkVIFAghYPiMK3nN5oYpIQDFV1ILbEeGj/PVjB1Is5yQJBHbmeHzvPwckG6L/HDqghCBYgdUuxsyzxWJIojFgqXVTYsQwrd8EQBUzeDYL8fWlnxiB1KtscwLJ41PwXzqU6KsRzC+QzlfGTtASFBk7ID3c1Sd1SqEWFB8JTUg4KRHzyOrp9hIgySUoM6M+C4OgpYdq5p8TvVz4UhjE8T5asUOUHxtNuT4939enp2THQhw/VBzjBwgdUMJWAWnalFmvvqQnwMyMd3cJiQChM+0TNcNaLrBahVCTDgSSPSYEy5fT5uZ+cpGGiSRBHZmxLcsLujQ18xtdk7mEkYQdc6KHUhTfG02gnRNBgrd0EkRVoWRr/OV44LUB2vE+jbn0aPIfA0wPgA23CIkJIpP7EBel1WvnK8TIuFIIDUgmKhkaCrySNHRQhJKmG688RRfg5YdW5M5Ol+TRgDnq8rYgaZF+AszgOyczOYdZdibd16Zr1k6X0ndUOqZ+RpkfABsuEVISIRPr4b5vBxzbJBLiIQjgURPkC68AKDnoSLFXBiSTIJk9gGxXhwELTvWzNiBDAWYZBEo85WxA81KAGkdgOycTBdNOUFiByi+kvph6Z9+Gyx5PYrYAYvkbm4TEgUCwjMuLJvXAABtmVStDomQhoazVxI9QcuptTzySFFQIQkloPNVnY9tw63gZcd0viaTIJmv7OjerChCBFJf2TnZgSDzLKvhFiF1IHCykqqjpdqbK0HfXGXsACFh8Ltsz5niazvFV0IAUHwlNSFA5quuQcCAaqS5qCLJJMQmBVKZ6I+nHgQtO7YzX3muSBSBnK8UX5sVEWL8s0KmjCAVRmqOWcikbghYDbe8x3hO09FS9RLlELFOMd3cJiQKZFyY++NW7ACdr4RIKL6S6AmStaSrAAAVCjNfSUIJuDjQ84AST/E1aNmx1XCLztekEcb5Gs8xEmcCGl+RZ+arAwHmWXS+kjqiBNxfztXT+cqGW4SEQgCe42rejh3gNZsQgOIrqQUiwMfMzOlTkaKbjSSTwM5XNbbCUvCyY/kkCjAJI6jzVckUxhNpGmTsSJCGWwbnCeUEuX4w85XUEWF+Rr1ccoApvtbN+RrfTH1CokBh7AAhoeDKldSAAIsC3RJf0xRUSEIJ43xNR3409SBo2bFmZr6y9DhpBHG+5ikwNTF+wgwgM59ZIVMOG26RxsZ2vvqcw2Wmc7Wdr+breWYi52UVHp2vhARGxg74O19bKb4SAoDiK6kFtvbqVQ4nYwfySCFT9R1vQpqAoM5XXY21+Bq02zkApBk7kCyCOl9j6gyPO0J4JsMDkHmRec1AhmO/lEDiUo6xA6RuBHW+ZqNwvgaJP8vPyVs6XwkJjID3ZaeQ+cq1PSEAxVdSE4I03JLiq4YUF1UkoQRwLhmGHCsxFZeClh1bma90vyWNAM5XNctmW02K4reKQ2HsV90Z1+wEjh3g2CD1QwQY43VruEXxlZDQ+O2JFzJf6XwlBKD4SmqB6cjwFl9l7EAeKQoqJJkEWTybmxRxbbgFBC07ZsOtRBLI+Zqn+NqkCPiPf9v1znlCGQHEJTbcInUm2BjX0VqPhlv5WXlL8ZWQwPhVrMwz85WQEjh7JdETZNJjNdwyUsxxJAklyOJZjhOk4ho74F92DACqZma+UnxNGEEyX3MUX5sUOf598iDNvGc23CqDDbdIE6AEGOM5NYLMVzpfCYkEaWb3z3yl85UQCcVXUgMCTHpMR5+KFFroaCFJJJDz1RRfY+p8FYC/sxEF5ys3ahJG4MxXiq/NiBLgz6sy79mZIJmWFF9JnZFNNb2fk4s08zWI+MqGW4QExTd2QGXmKyHFcCSQ6DEnPSJAObWKFBdVJJlYDVM8NynkDnJcG24pARZmQLEAw0tYohAB/t5suNXECN/xb7veuUlbRpDKCW5MkPoihPDdYIlEfA0yPlQ6XwkJi5+bfS5nOl/TdL4SAlB8JbXAXjB7ODKs2AFmvpLEEjyeI96xA0EabukQgpmvyUN4O/sAKTDR3deUSAeNfzMeAKyQKYexA6QJ8CtRBmSuc9VjB6x1iNdb0/lKSGj83OzzqoaWtAKF83VCAFB8JTXBWhR4PMV0vuaRYpYbSSaMHUCARsgAZOwAHfIJJMgHhA23mpYgQ9pquJVJc/yX4Fc5oamAobHhFqkrQngvBQzDQE6LMnbAY/POariVbqvuexMSYwSE54ZKNq+jrepOdkKaF44GEj0iSDmc5XxNs5SYJJQwDbdiKr4GKEkELPGV54nkEaDhlpqN7fiIOwICuq8rzmq4xfFfio+4pOXkbZobE6R+KEJA97DJWc721nrEDrDhFiGh8dtQmctpaG9h5AAhFpy9khoQJPO1EDvQQkcLSSKBnK/SIR5b56uAr/gCyMxXOl8TCBtuxZogf96cSvHVEb/rhyW+cmyQOuK3fWaN76rHigRquGU6Xxk7QEhg/EwT86qGtgzFV0IsOHsl0RMk89VquGUodLSRhJPgzNeAz1N1HSnGkySQAM5Xxg40LYoI7nxl5ms5Ps6+mDdrJM2B4iPU2LEi1b6+B6nAy8/LWzpfCQmMX47zfF5jsy1CiuDslUSPOenxnEpppviKNNIUVUgSCeV8jecC2m9hZsHYgYRC52u88SlfBIrFGY7/EuyGQm7iq5UXHs9rB2kSfKpbbOdrVGINna+EVBXFL3Ygr6Mtw+s1IRYcDaQGBNhxNhcGsuEWP5YkiQQfJ0mPHdAYO5BQgjhfsxRfmxTFLzwOxZmvHP8l+DUUinleOGkOFOE9bgviaxTrAJ/rR35ObmJwjBASGOFTsTKfZ+wAIcVQ5SLRYzlfvbqMaoXMV4qvJJEEcb6aDvHYxg4EcL4BQF7X6ZBPIoGcr3kunpsUAf/NF6shT4bdk8vwix2Id9UEaQ78NlhzUW6uCMXH+TonXa8+AjEhpICMHXB/PEvxlZASOHsl0RMka8nKfEWKogpJKHS+yuD+AM5Xnc7XZBLE+ZoD0q01ORpSXYJsvuSjasjT7Pht3sW8WSNpDvyihSzna2sUmytCuDvDARk7wLxXQkLh23CLsQOElMDRQGqAtSjweEqR+JphliNJIoGcr/EuHfXbQbdQNQNpii/JI7DzlbEDzUiQzGdmvrogfH4feryrJkhz4Odut5yvdYsdoPhKSCjktMx9XM3lNbTT+UqIDWevJHps52uA2AGDzleSVII7xOPqXhJCBIodUHWdztdEEsD5qmZjuzkRd4LEDjDz1Y2Ama+MHSB1xO8ab2e+piIQa/w279Q5NtsiJCR+szJmvhJSCsVXUgOszNcgDbfSFFVIMgnifLXF13hOZBSfHXQLTTeQ4nkieQRyvubofG1WAvx5C5mQnL6W4Bs7EO/IGtIc+Lnkot1cofOVkGrjV7FC8ZWQUjh7JdFjl8N5iUqafGoqDcGwe5JIAjhfExA7oAewvuYZO5BQfBbPuiYfp8DUlCgBMp/zkZYlxwE38VXOsRg7QOqJ4rPBYjtfI8t89RFf0xRfCQmDXxO9+byOVma+EmLD0UCiJ0yWJUviSFIJ5HyNt3tJliSy4RZxwW/xbG9O8DrSjAQIlbAbbtH5Woa1yc3YAdLACAhPoSYbpfjq63xlwy1CwuLVKNMwDOQ0Ha1pOl8JseDsldSA4F3cjZg6+gjxJ4jz1WqaEs9xErThVl5j5msy8fmbx3xzIu6Ea7jF8V8CYwdIE+DnfLWd7VFsrgjF3/lK8ZWQkLhft63NlFZWqhBiw9FAokcEyHw1XRmCCwOSVEI5X+PpXhIBxBfAdL5SfEkegZ2vvI40I37liwAzX93x2byz88Ljee0gzYEQwjNaqO6xA2y4RUgovHo1WNdriq+EFOBoINETKPNVLgwEy0VJYgniEI/3AtqvGYeFqhtIKbx8JQ+fslGWVjc1fp3QgeKGPBz/JdixAy6/QbtqgmOD1A9Zouw+ynORZjqz4RYh1UbxuG5HuplCSJPC0UBqgOl89RGVdAikuDAgSSVMNnJMnX1BMh8BQNV1ZBg7kDz8nEuWMzzVUpvjIVXFy0Fjkdd0pBSBFMd/Kfb1wyXz1d64i+e1gzQHfqdwW6yJJHYgiPOV4ishYVA8KlYiHc+ENCkcDSR6RJAsyzx0kWaOG0kwAT77MXe+Bsl8BABVMyi+JJbkbk7EHRk74P2cvGZwnuCIX+wAXeGk/shrvPsgt53tbLhFSFMghIDucuGm85WQhXA0kBoQIPNVV6EihTR3x0hSofM1UOYjIGMHWHacQHydr3T3NTN+wgwgF3Mc+w74XT9i3qyRNAcC3hss2Uidr/AeH3qema+EhMTLNJGl+ErIAjgaSPSIALEDWh6aSHNRRRJMkMzXeHeslnlw/mg6na/JJGDmK+NrmhI/YQaQzjg273DAL1s/5lUTpDnwyocEoi5T9rh+qHPyls5XQkIRJHagNZ2q5SER0tBwBkuiJ2DDLR0plhOS5BLI+Rpv95IIGjug60jzXJE8gma+xnRzIu6IAM7XvEbnqzN+ma+MHSANgE91S17TkVYElCg2V4Xifv3IU3wlpBIURbhumuY0DQCdr4QUw9FAaoj3ollFCmm62UjiCVBWLeJ56pZVgQFiBzSD54pE4ud8jffmRNwJkvksM1/jef5bFPbmncvjMY+sIc2B4lPeklP16IQaIdw3J/Kz8jZN8ZWQMHjFhUUaI0JIk8LRQKLHih1wm/QAgKZCFWlmvpLkEsT5quelq0/EU3gMGjug6gZSCs8ViSOw85XuvmYkSOZzTtNZIeOIX8Mt6UCiK5zUExkt4j7Gc1qE4qtn7EBW3qZbI3pvQuKJ16YpG24RshCOBlIDgnRxl85X7o6R5BIg81XLx9q5FKThDgCoFGASStDM1/iOkTijBNh8ybPhljNWNYTb+dPemGD2Hqkffu72nKpHtw7w2rzTcvI21RLNexMSU4JlvvKaTYgFRwOJHnNR4Bmzr6sydoCCCkkqgZyvaqydS0Ea7gCW85XnisTBzNdYI4Twdb7mI3XGNTH23p1LhRE3JkgD4Oduz0Wa6eyxeUfxlZCKUDyu21k6XwlZAEcDiR4rdgCGu6tNy0M1UkizlJgklSCN6bR8rDu5B2m4AwCaztzHZMLM1zjjp60DzHx1xy92wBwbjOQgdUQITxsGcqoenUvO0/nKawchlSA3TZ0fo/OVkIVwNJAaUCy+ujzFdL6ylJgkF59u1UD8na9BM181Ol8TCTNfY02QhlvMfHXBr3LCFl/je/0gjY9fU81IG24Fcr5yfBASBsW+9CwcWzmNzldCyuFoINFjO189hBUtb8YO8CNJEkrg2IH4CksC/uILAKi6jgzF1wTCzNc449eMB5CxA3S+OuBXOaGr8jmsLiJ1RFG8pziRjm/h8eaMHSCkIhRz7eLkfrUbbvGaTYgNRwOJnqLMV9cdbz2PPJ2vJNEEbbgVY/FVeLtiAEDXDegGkKKIkDx8na909zUzik9JMmBmvnIh54BP5YSWj/XGHWkOBLxznXNRZjp7XT90xg4QUgmWD8JpXOeY+UrIAjgaSA0oih1we4quQTVSyFBQIUklkPM1H2thycfXCEA22wLA5nyJxM/5armXKDI1I37NeAAgrzLz1ZEgsQMxvnaQ5kDxiRbKqVFurgSIHeAYISQUwna+LhxbWVUDQPGVkGI4Gkj0mCdmxSvzVcsjZ6QoqJAEE9T5Gt/FgaL4dzvXLPGVsQPJwy8U2I4dYOloMyICZL7mNR0ZLuQcCNBwi5sSpN54NOcBIs589Wy4xdgBQirBih1wGlqMHSBkIRwNpAYUO1/9Ygf4kSQJhZmvZjMO7+fkdTmZY8OtJOLjfLUbbsV3gyLOeDXusGDDLReszFdXcYmxA6T+KD7RQjktSme7l/OVsQOEVIJX7EDWjBGx3LGEEIqvpBaIwsfM3fmqIm8w85UkmQDO15iLr/AxNgKApslncKMmgfhlvnIB3dQIuDfusGDmqwv25p1L5mvMI2tIc+C3wZpTNbRG5nz1eHPb+coxQkgY/BputfJ6TUgJHBEkekTB+eqKriJvKEjzJE2Sir149nhO3GMH/MrKQecrCeJ8jfEGRYwJ4nzNR+qMa2b8Yge0WF87SHMgm+rVqeFWkMxXxg4QEgrh4XyNNEaEkCaFI4LUgKLYAZd5j6HnkTMUZCiokMQS1Pka3wW0gH/DHWa+Jhhf56uV+RrfMRJnCos49+fkVZ3iqxN+sTVaHlBStTseQhwQAtBdzNmA1VAvomu7ULwb0gEUXwkJiZ356jCuKb4SshCOCBI9xQ23XHed88gjTecrSS5BMl+1fKybpgQwvkI1Ywd4rkgifpmv5gI6xhsUccbKhfNzxmXS3HhZgF/mK2MHSAMg6ul8FcI9lsNyvrJqgpBQeGa+UnwlZAEcESR6hL/zFVoeqpFCmpmvJLEEcb7GewGtCOFZcgwAKp2vySWo85UOv6bEq2uyBTNf3fCLHYh5XjhpCmR1i/vjOVVHSyqq8zdjBwipNopiZb46xw5EluFMSJPCEUFqgLD/7zbnMnQVKlJcVJHkEsj5qsa6pNpvYQYAqiadK9yoSSJ+zldzc4KddZsSr+w4QEaO6Aab7TniGzugxrpqgjQHfrnukZYpe23esVkjIRUhvBpuRZrhTEhzwhFBoqfE+eruylCRopuNJBcRxPmqxtvVF0A0y1uxAwovX4kjiPOVi+emRfHRD/PmxgvFVwf8rh8xzwsnzYEQ7psrhmFIsSayjVUf56tQ4j2/IiQCvBplSic7r9eEFMMRQWpAkfjq9hQtL8VXnqRJ0vESl2IfOyBvvaIHVN0SYLhRkzwCZL7GeHzEHQH38kVAumgAjn1nrJOnS6alnmfsAKk7ihCuZ3BrY7U+ztccIwcIqQDFy/nKzFdCFrCoESGE+KgQYocQ4mEhxI+EEH1VOi4SJ8xGEJ6Zr7qKPFJcVJGE4yMuxdzZVxBf3J+TZ8Ot5BLI+UqBqVmxK+ddHs+rUljkYs6BQLED8b12kObAy/lqba5EN7495le6SvGVkArwbLil6WhJ001OSDGLvcL9BsBphmGcAWAngPct/pBI7CiKHXCb9whdOl9ZTkgSjZ+4FHNnnwjifLXcb4woSR5CQZIb0sUdu+GWi3nT2njhPMEJNtwijY8Qwj1WRI04VkQo3s5Xjg9CQlPIfHUQX/MaG24RUsaiRoRhGL82DMNMKcedAFYv/pBI/ChuuOUw8TEMCCvzlYsqkmiCOF/ju0BQfJxvAKDqdL4mF+GuzAGxd4bHHb+GW8x89cCsMHIVlxg7QBoAAffN1cidr8Lj+sHYAUIqwt40ZcMtQgJRzRHxJgDXV/H1SFwwT8wKDOdyYl0DAKhGim42kmwCOV/ju4D22kG3sASYNCNKkgcbbsUaexHn8jgzXz2wywbcxCWODVJ/FOExvq1Ykcg2VzzOGxpjBwipBK/YgZyqo5WbpYSU4LuKF0LcCGC5w0PvNwzjJ+Zz3g9ABfBNj9d5K4C3AsDatWsrOljSpJRkvjpMu/Q8AEBFmm42knDYUAjw1tdUq/RY4bkiefiND8YONDNBna/snuyEX+yAFuuNO9IcCCFcx3c26kxn34ZbHB+EhIUNtwgJh++VxjCMK70eF0JcB+AFAJ5teAT1GYbxBQBfAIBzzz3Xq6qUxI7CosDxD69J8ZUNt0jiSXhDIRFg+Ks6na+JRXjYpgA2FWpyhEf5IgDkVWa+uuLXcIuxA6QBUDymONFvrnhs3jF2gJCK8No0ZewAIQtZ1ExMCHE1gL8FcJlhGLPVOSQSO+yGWy6TLl3GBrPhFiHJdvYpgWIHLAGG4mvyCDI+KDA1K3bms08mZIaLuYVYma+u4hJjB0gjIJzjx1AUOxCZ8xUemxPcuCOkEgqZr04Nt3RWqhBSxmJHxKcAdAP4jRDiQSHE56pwTCR2WJmvurP3tUh8TTPzlSQZL+erYcR+gWB75L1iByznK2MHkgczX2ONgHv5IlDccIvzhIX4ZL4ydoA0ANL5WqeGW37O1xhvbBMSFZ6xA5qO1gzn6oQUs6iZmGEYm6t1ICTG2JmvcJ73aFbma4qZryTheCwOzE2KOC8Q7MpZj+dYzlfGDiQRZiLHGdv56vI3ZuarB4wdIE2A1/5ZXrU2V6Jyvio+ma+MHSAkLG4NtzTdgKYbaEml6nBUhDQunMGS6LFjB1yWVHpBfKWjhSQar5WJLb7GdyLjVb5kYTfcogCTPLzKRoHYZyLHnUJ2nPPjBecrx/5CfOZOMa+aIM2BcF8JIBu181UId2c488IJqQgrq10vG1qRx4gQ0qRwRJDoscRXYTivmzUpKuUNZr6SpOOxgDYd4klYILiJL0Bx7AA3apJHsjOR447w2XzJseGWO1bmq6uzj85XUn8Uxf36bos1dWu4xWsHIWFxc75SfCXEGY4IUjPkfrd75qtG5ytJOoGcr/FdIIgAuQOF2AFevhIHM19jTcH57vy4HTuQ5jxhAfa50y3zlZEcpP4ICI/NFfnZbY3U+crYAUKqidt1O6tpACi+ElIORwSpCToUKb46zXvM2IE8UmyiQ5KNUODZrRqIdVm1X+YjAKhsupNggmS+xnd8xB1rRJc7aCwYOxAEr27uHBukvnhmvkY+vn0y9blxR0hohIvzNZuPeDOFkCaFI4LUBiHcpz0lDbcoqJAk45FJZm5SxNm9VBBf3J+jmg9yoyaB0PkaaxSfynmKrx74Ndxi7ABpAIQQrttnkZcp+zlfYzy3IiQqLOfrgtgBjeIrIU5wRJAaYcbsO018zHJqFWl2MSbJxquhkBU7EGNxyS/zESgWYLhRkzyY+RpnBJwXcRY5Nttzx858ddi8MwzA0Ci+krqjCI9M56gbbvlmvjJ2gJCwuDXKjD7DmZDmhCOC1AQDgOIaO2CJrwpzHEnC8VocWJmv8V1AK/6Rr1A1AylFFPJhSXLwdb6ydLSZ8Yt8znMx54F1PnTa4JbZe9yYIPVGwL/hVmSbK0JxryzitYOQilCE87WHDbcIcYYjgtQGITNfHbFiB4w0YwdIsvFsuGXFDsRXfIVL+VIxeV1HWuF5Ipn4OF+1XLzHR8xRfJzvtuudDbcW4hU7YDdr5JSf1BdFCNdM98jLlIXi03CL4ishYSnEDpTeH72TnZDmhCOC1AjhXlFd1HArw8UBSTRezler4VZ8Fwi2pOKhr+VVg2XHScXP+arnWTraxLiVL1ow89UDK3bA6eRpWM5XbkyQOiMA3cV8GnmZspLycL7y2kFIJVheCL3swm013GKlCiGlcESQmmCYopLjjrdmxQ6kmONIkk0g52t8xVfb+ebxHFXX6ZBPLH6Zr8y1bGYKzlfnx63MVzrfnbCcrw7ikh7/yBrSHCgecUE5VVa1KFGNb+HT0DTGG9uERIVwdb7KTb/WTKrWh0RIQ0PxldQGIaDAcHa06AXxNcVFFUk0ATJfU/FdQBecb14Ntwyk6ZBPJr7OVzXW4yPuWFd/t/Gf13S0pBTmPTvhGTtgOl8FF8GkvsjMV/fxHamr3TPzNRfrjW1CosLu1WC4ZL7S+UpICRwRpCYYEBAwnLPcirIsuagiicbT+Rp/95Id2++hr6maTod8YvFzvqqxHh9xR/g4X/Mqx747QRpuUXwl9UURwnV8Z1U92nxIN/HVMMyNO8YOEBIWy6lebq7KsuEWIY5wRJDaIEzx1ekx09FncNeZJB4PcSkBsQN+3c4BQNUNxg4kFSG8Pxy6SndfE6P4ON/zmo4MF3LOWJmvng23uDFB6osQ7uM7m9fRlqmD+JqAPH1CosLtum05XyNroEdIk8IRQWqEf8MtlouSxOPlfLVjB+K7QLCzo9w67sAUYBg7kFA8NicMQy6sKTA1LX7O15zGZnuu2DtXXpmv3Jgg9UUI4bp/Nq9qaIsyH9JVfM3J2xjPrQiJikLma5n4qtH5SogTHBGkNggBBTocF87mrrOIsaOPkGAEcb7GV1wK4mdVNTpfE4tnLAc7ujc7dnacyznQynwlTnicEw2ODdIYyFO48/iez2toS9dTfGXsACFhcWuUmc3T+UqIExwRpCYY5kfN2fka/0ZChATC0/ka/9I4P+cbAKi6zoZbSUUocN+coLuv2Sk03HN+PM+8Z3eCNNyi+ErqjOIxxZmvV+yAHv+qIkKiwjV2gM5XQhzhiCC1QcA989VeNHPiQ5JOsjNf/ZxvAJDXDAowSUUI927VzLVsegqbL3Xqht7MWJmvjg231LLnEFIfBIR75quqoTVy56t79R2vHYSER7FjB0rvtzJfWa1CSCkcEaRGmA23nOZc5sRHScdXVCIkEF4NhRLgXvJzvgGm85WTuWTi5lwCKL7GALdFnEVOZearL47OvvhfO0hzoHhMcebzOlojdb66bN5ZsRxs1khIaISb81XVoQhwvk5IGRwRpCYYEFBgODvaTEefwpIfkng8nK9a/BvTCXg73wDpfE0rdL4mEy/nqyUwcQHdrFij2tP5yhJGZzxjB7gxQRoDIYRrQ835fJ0abvHaQUjFKC4VKzlNZ+QAIQ5wVJDaIBR356u5MBB0vpKk49lQKP6xA7Z+4PEclaXHycWtbBQoairEBXSzYi/iXB6XDbe48eKMLV0vfIh5yKRB8Cruyap69OKrJbQWYwmydL4SEhq3ipVsXmPkACEOcFSQGiE9bc6xA3JhkKLzlSSeIM7X+I4Tv8xHAFB1A2kKMMmEsQOxxi5fdHHGMfPVAyvP1encaY0Zjg1SZwSE6/5ZNq+hLUqnnEjR+UpIlfFquNUa5WYKIU0KZ7GkJhjCzHx1iR3QoCATZdA+Ic2A6w4FEiEuFcqO3Z8jYwd46UokbLgVa/yc7zmNma+u2L88j27uFJdInVGE++bqvBp15qvL5p2d+cpzCyFhEW7OV1Wn85UQBzgqSM3warilIs1sGEK8nK8JEJf8yo4BK3aAztdEIhQkeXzEnUL5oovzVaXz1Z0AsQMsqyZ1Rgj3hnrzeQ1tUZowmPlKSNVR7LjxhQ23WrmuJ2QBHBWkNpiZr47oGjSkeJImxCvzNRGxA/LWTXwBrNgBnisSiVdpNTu6Nz1+zve8pqMlzY0XRzwbbnFskMZAEcKxAs4wjBo13HKK5bCcrxRfCQmL26ZpTmXDLUKc4KggNcIj81XPQ0WKjhZCAjlfYyy+mrfesQM6MgoFmERii68epdUsHW1aFMXKfHZ+nJmvHgQZGxRfSb1xcb6qugHdANrqETtA5yshFWOLr2VDK6dRfCXECY4KUhs8M19VaEjxJE1IEOdrjBcIhYZb7s9RNTbcSi5Bci0pMDUr1qh2jR1g5qsHXrEDFJdIY6AI4fgRnc/Lz2i0zleXzHDrPjpfCQmNW8VaNs/YAUKc4KggNUK4Z77qKp2vhADwdr7mpetVxFd4DBY7oDN2IKmwtDrWCJ/M5xydr+54jQ2D4itpDAScr+/zeSmARirW+DpfeW4hJCxuFSt0vhLiDEcFqQmGUKAIw1lU0TVoUHiSJsTP+RrjvFeg4N3yIq8ZjB1IKp6l1RRfmx2/zZe8pqOFrndn7LgNj4ZbHBukzsjM14VYztfWyDNfvSJruDlBSFgUl+t2TtXRws1SQhbAUUFqiGPoAKBrUKHwJE2Ip/NVi/3iOVjsAJ2viUUEiR3gArpZUezx7yK+qnS+uuPlCqe4RBoDIZw3V7KqPKdH33DLKXaAznBCKqXQcKv0fjbcIsQZjgpSG4RXwy0VqkHnKyGezlc9H3vx1W0HvZi8zszXxEJ3X6xRPPRDwHS9c57gDCM5SBMghHD8iNqZr3WNHeD4ICQsbhUrMnaAGxqElMNZLKkRMvPVcdFsSOdrhoIKSTpCgavzNQmxA5Z+4PEcVdORYTZbMgnU0Z2T/WZFwNlBA0g3LDNfvWDDLdL42J/S8uY8ah1jByznK53hhITGrWKFsQOEOMNRQWqEgOLScMvQVGiGgpYUJz4k6bh04wWkuKTEXHyFd9mxrhvQDdD5mlQCia90LzUrBfPmwvGvmoosM19d8HS+cmOCNAaKS7SQ1XCrPs5X8z6OD0JC4xo7oOloSfN6TUg5FF9JTTCEAuGS+arrGjSkkOFJmiQd34Zb8RaW/JyveXORRPdbUvHIfLXuo/jatBTKFxc+ltc49j0JlIfMsUHqi1uJsuV8jTTzVUn5OF95biEkLG5xYaqmI80qNUIWwFFBaoOQsQPOcWR5aBAsTyAEHhsQSXC++jTcUTV5f1rhRk0isZ2vdPfFEa+GW3lV3kfx1QuXho0GMy1JY6C4bLDaztdIYwdcKosYy0FIxQgX56uqsT8DIU5wFktqhNVwa+HCwNCk87WVjTRI0kl4w61CHpzz47b4SgEmmQQSX+M9RuKMLb46PJaznK+cJ7jjdv3QmWlJGoOCUFP6ObUbbmXqEDvAzFdCKkZxiQvK68xoJ8QJjgpSG4SAgO64qDJ0FRoUnqQJcXMuAYCmxj52wEt8AYoEGO6mJxOWVscat5JkoBA7wMxXD9waNtIVThoEt2hiy/naGmV3dNfMVzpfCakUxWVDJa8ZnKsT4gDVLlIjLOfrwkcMXYOKFFroaCFJx22QAKbzNe6xA/JWdwp9BKCama/MkUoonuIr3UvNjuIizADMfA2GX1k1NyZIfSk01Sy9v5D5Wg/nq3kfrx2EhMap4ZZhGNB0g3N1QhzgqCC1wc58dYodUKEbdL4S4u18zQOpmIuv5q2r81W13DE8VyQSuyEK3X3xxNlBA1B8DYRr7ABd4aQxKGS+lscO1CLzlc5XQqqNU8VKXrMy2ul8JaQczmJJbRByv9vJ0GboKlQodL4S4pn5mqSGW86P2+JrlO4Y0rjYma9098URL+drjg23AuCyeceNCdIgFISa0vutzNdIN1Z9M195biEkLIrDvN2uUuP1mpAFcFSQGiGgQIfm5nyFghaepEni8XC+6mrsF8+FPDjn30FWrUEuHGlgmPkaZwqZzx6Zr2k6aVwRilu2k7zl2CB1piDUlOdD6sikhL0BGwluDRvpfCWkYhSHuLA8N0sJcYWjgtQGoUjnq4P11TCY+UoIAG/nK2MH7Fw4nisSitviGaD4GgMKmc8LH2PsQACEW+arOTbo7CMNQvlSQK1FPqRb5YTBvHBCKsUp8zWvszkuIW5wJkZqgtzNlgHcC9A16GDmKyGezldDi72wpCjesQPZPDNfEw1jB2JNwfm6kBzF1wC4LHR1VQpLUboKCQmAYpe3lN6vagbSUQs1bg0b6XwlpGKcMl9VM/OVDbcIWQhHBakNZsMtp0YaYOYrIRLPzFct9s4Ma+nleJ4AkNUoviYaT/HVcr7ys9HsODfcYhmjL64Nt+K/cUeaAyehBpAZkWklavHVPHdYYquFdT2J+fyKkCgQQpiXnuKGW1bmKzf8CCmHs1hSIwQUV/FVgwaF5QmEeGa+arEXllxMMTaW85UbNQnFzbkEMHYgBiiK+wkgb+Y9MxveA9du7irHBWkI3Nztec2IvjmP2+Ydna+ELApFiJLYAVW3Nku5riekHM5iSW0QCgQMaA7rAugqNKToZiPEy/lqxN/5anlf3RtuWR2R4/57II54ZVYajB1odhQXVxxQlPnKhlseuGze6RqFJdIQuDlftZo4X80x4Jr5yjUIIZWgiNIxzYx2QtzhqCA1QQgBAUBzWFQJQ4fKzFdC4O98jbewZBvfXH4FOZWxA4kmUOxAvMdInBFY2LjDgpmvARBwPnkaFF9JYyAs52tdMl/pfCUkCgRKna927EDMq/UIqQSOClIbrMxXx4ZbKnSDma+EeGe+qrFfHNgLMxcBOmuJrxmeKxKNV8Ot2LvD40shdcA985WxA164OV8ZO0AaA0teLa9uUXUDmaiFGjfx1eC1g5DFUJ75qmqMHSDEDc5iSU0QZuyAUzmhMDSoSHFRRYiX89XQY784KCzMnB+3xddUvH8PxAV78ewiMAkl9rnIscYuSV74EMsYA+CV+RrzawdpDtwyX1VdR6pWDbfofCWkqsjM1yLxVbcabvF6TUg5HBWkNtiZrw7iq65Bh4IMna8k6Xg6X+PfcEtxKUm0sDNf6XxNJn6xAxSYmhpFuOeOFMRXOmlccbt+6Dqdr6QhcMt8rW3DrbIxYl1PeP0gpCJk5mvhe6tSJRP1hgohTQhXsKQ2WLEDLnlkKhQ6XwmBx0TFiH/mq9vCzCLHjufJxk98jfn4iDuW+OqY+apaDbc49t3xih2gsETqj1uuu6YbNWi4Zb05na+EVJNy52uhQSav14SUw1FBaoIwW2loDmtmxZDOVwoqJPH4Zb4mxJnh8htAVtWRSQko3E1PJm6LZ4DuvhhgjWqnzRdmvgZAKO6RHBSWSANQaKpX7nzV69dwy9AAiML1hRASivKli5X5GvmGCiFNCGexpDYIAQUGNMfMVx26SFFQIcQr81WPf8dq39iBvI7WdLx/B8QDa/FMd18s8Rr/zHwNgBDOGxMJqJogTYKL81XV6thwKwFzK0KiRFFEScMtXq8JcYejgtQEIRQIYSzocAoAwkiOo48QT7ycr0louGUvzFxiBzQNrSxjSi6MHYg3HrEjeU2HIhB9U56mxit2gGOD1B+3DRZNN+rXcMvQYj+3IiRKZOxA4XvV/CZyNzshTQhXsaQ2mJmvjg23oMPgwoAQE4/YgZi7M2zx1eVx6XzlZSuxUHyNNV7aS07T6aLxw7XhFsUl0hhYQ9wou8rn9TrGDtD5SsiikA236HwlJAgcFaQmCFNVcRJfFe46EyLxzHyN/wLBN3ZA1dFC8TXBeKjzCRgfcafQcMvB+aoazHv1Qyhwdr5ybJDGwEoWKF8K1KbhliW+aqX3J6CqiJAoEWXOVyujPfIoEUKaEI4KUhuEgAJ94aJK16HAAFJ0LBHimfmagE0Kr4Y7AJBVNWa+Jhlf5ys/G82MsGMHFj6W13R2TvbFzflKVzhpDKyGW+XRQnnNQDrqzRXr+uDofOW5hZBKUUTpmFZN5ytjBwhZCK82pCYIoUAA0MrXzOYOtOCimZDEO1/9Ygdyqo7WDC9bicX+gLCpUBzxa7iV4ULOG9fYAW5MkMbA7RqvanoNna9l756AjW1CokRmvhbFDjDzlRBXuIolNUGYma8Lna9m+Q8nPoR4lI3q8v6Yi0tCOLtiLLKqztLjJOMlvtLdFxucnO/MfA2CS+WEoXNskIbA7Rqv6TVwvrpmvnJzgpDFsKDhlpX5Skc5IQvgqCC1QShSfC2vJ9RV+TBjBwiBLBt1cfUBsd+ksJtxeGS+0vmaYKzFMzu6xxLL+epEXmPmqy90vpIGxzK3ln9M87qOTOTOV5fNOzakI2RRCLeGW4wKImQBHBWkJgghoMCA5lTuA0Bw0UyId7dqIPa5ZLYrxiV4IKfqzHxNMp6Zr/GP5Yg7lvayYJMWQF6l89UX4bJ5p6sUl0hDYGW+Lmi4pRlI1Sx2oGyM0BlOyKJQhChZulgNtyKPEiGkCeFMltQEYZZTL3S+WuIrP4qEuJeNWuJrvBcIbq4YC9lwi+eKxOLXcIsCU1Njbb64N9ziQs4bl+sHXeGkQbCv8WWf03xdYwfYcIuQxaCUOV9VU3zlhikhC+GoILVBCCjAQuerHTuQqf0xEdJoeJWNArEXl9xcMRZZVUcLxdcE46HOU2BqetyEGYCZr4Hwqpzg2CANgLDd7aX317bhVrnzlbEDhCyGBZmvug4hEL2bnZAmhDNZUiOkrKKVG5Zs5ysnPoS4O5cs52u8x4kdyebWcCuv0/maZHxjBygwNTO+zleKr94IhZEcpKFxixZSdSP6zuiezleOD0IqZWHmq8FmW4S4wJFBaoMQUIS+UFQxHX0KG24R4u5cshYLCXFnuBhfkdOY+ZpoKL7GHiHgeA5kw60geMUO8LxJ6o9bU01VM6LfXKHzlZBIkJmvpQ23MlFvphDSpHAmS2qDUGTsQLmlxcyyVBg7QAiS7nxVCnXHjmTzGmMHkozwix2I9/hIAuXlixZczAXAdfOOGxOkMVAs52t5wy29jg236HwlZFEoQpREiaiaHn2GMyFNCkcGqRECAoZD5qslvnLiQ4hcPDvcb2W+xnyBYC29dLfYAZWxA4nGWjyzqVBsEXAe/zmVsQP+eDhf6ewjDYCd+Vo2xvO6jkzNxNdyE4jO8UHIIlgQO6Ab3CwlxAXOZEltEEKenMstLTqdr4QUcFk8mw7xuC8QhIfxVdMNqLrB2IEkY39AnGIH6HyNA4oQjuM/r+nIcOPFG8/MV25MkPpjO1+L7tN0A4YBpKLOiLSVX630fl0DmE9JSMUsaLil6UhzTBHiCEcGqRmKo/PVynzlopkQz27VQOzFJbeSREA63wCgNcPLVmJh5mv8Ec7OV2a+BsDr+hHzawdpEhycr6pZrxx9wy1zDDDzlZCqoigoy3w1kEnT+UqIE5zJktogFCgwFma5MfOVkDI8Gm7FXFzyih3IqvJcwdLjJOPhfDUoMMUBxcX8z8zXILj8fhjJQRoEpw1WVZPfpJn5SkhTIp2vZQ236HwlxBGODFIbhMx8LY8dMDQ6XwmxcXUumZmvIuanbI/YgZwmF0xsuJVg3DL7AApMMaF8EWchxVeOfU+EwmZ0pKGx5FWjxPlqiq9Rj2838ZXOV0IWhVgQO2BE72QnpEnhTJbUCJn5qpWJr3k1DwBIp+l8JcS9YUqyYgecBIS86Y5ppQCTXDxjByi+xgHZcGvh/Wy4FQABD1c4xwapP06Zr6q5sRq5s93V+arHfm5FSJQoYmGUCDNfCXGGI4PUBtP5Wp75ms9L8TWV4sKAEFfna1Iabpm3buILAOZIJRmKr7FHEcLxFJjXDLreffHYvIv5tYM0B3bPK32h8zVVr9gBQ4t/VREhEVJ+3c5rBmOCCHGBVxtSG6zM1zJVRVXN2AE6XwmB++LZjB2Iubgk7Dw457JjAGhhRElyEXbR6sLHmNsXD1wbbjHz1Re3zTstD3CDmzQAwiFayBJfI8+IZOYrIZFQ7nxlTBAh7nBkkBohHMsJVTUHAEinuTAgxD3z1Wq4Fe8FguKV+arWqDSRNC5+zle6+5oeO3qkCF03oOoGF3N+CAWum3cx37gjzYEw61tKSpTNjdXaOV/LxggzXwlZFKIsq52Zr4S4w5ksqQ0usQNqXjr6GDtACODqfE1M7IC1MFv4mNVwK8PS4+Ti2XCLuZZxoNxBAwB5nc32giEcSqoNM/OV1UWk/igOxQuFhlv1ynyl85WQxSCv24Xv8zqdr4S4wZFBaoQUXxfGDpiZr3S+EuLhfLUabsX8lG3323IoOzadr2y4lWSsDwgzX+NKuYMGKDTba+HY98bp+mFF1nCDmzQAVrRQeWd0ANGLNcLl+kHnKyGLQma+ljlfo3ayE9KkcCZLaoNQoAgDWrn4qpnOV2a+EoKkZ756zdXofCWFxTOdr3FFcdAP83bkCMe+Nw7XD01ucHNskEbAusaX50MCdWy4pet0vhKyCBQhSp2vmo40r9eEOMKRQWqDsDJfSxcGWl4uDDIUXwlxd74mJXZALMyDsyg03OJlK7H4Zb5yAR0DxILYEWvsU3z1QSgOzldLfOUci9QfxRRYiyPILFNG5Hnu9vVDK73f0AqPEUJCIxwabnGuTogzHBmkRpixAwsabklHXzrDhQEh7s5XK3Yg3uKSHQfnlPmq1qg0kTQuvuIr3X3NjtRmSk8AtuudDTy8EQ6Zr9a1I8U5Fqk/VimyphWVKOuW8zXq2AFmvhISBeXO15ymM6OdEBc4MkhtsBpulamvmlkSl2bmKyEezldzsRBzccmuKnd4zBJgWtIUYBKLcOjWYkHnayxQhIBepo3Yma9czPngFTvAsUHqT9oUWFW9NB8SADJRxw5YY4CZr4RUFRkXVBjTOZXOV0Lc4MggtUEIKDAWxg6YzlfGDhAC+Ga+xrw0TjHFNSf92cp9bElxkZRYvDL7YMR+cyIJlJcvAowdCIxjwy3GDpDGIW2614uNGJYQW7/MVzpfCVkMSlmjzJxK5yshbnBkkBrh4ny1Ywe4aCZELp4d7k9I7ICFU+ZroeEWna+JxW3xbCRrfMQZRYgFp8AcG24Fw2lzztq4Y+wAaQAsgVUtsrdbmyuRN+ixrx9lZxhDp/OVkEUgyipWcqrO6zUhLnBkkNpgNtwqF191syQuk2mpw0ER0mi4OF8T03DL/TE23CJ2KvAC55IpMNH5Ggvcna/cePHGIfNV49ggjUPGih0oynytfcMtJ+cr5xWEVIpSVrHCzFdC3OHIIDVCikrlG86qxtgBQmzcMl9t52u8F9CF2AEH56vlfuOELrm4OZcovsYGRcGC/Sc785UbL954xg5wbJD6k3KIHbDGd/SxAy6bd8x8JWRRKELYlx7DMJDXDIqvhLjAkUFqg1CgwIBWtjAwLPE1Q/GVEPfM12SUVVtLL93hV5Cj85W4OpcovsaF8uw4oMj5ysVcAFw2Jhg7QBqAtB074OR8rVXsADNfCakmilJwvlpz9VZerwlxhCOD1AbhkvlK8ZWQAsKhbBQoih2I9ylbeDbcqtECjTQurs7XZMRyJAGBhZsvOTbcCoZQHGIH6HwljYNT5qv1dd0abtH5SsiiEEWbpjmVRglCvODIIDVCmIuqssxXleIrITa+sQPxXiBYay/Dwf2b0zSkFBH9Ao00LnYosIv4GvPxkQScGm7lVWa+BsIxdsAaG5xjkfrjlPlqxQ5kos5ddXW+6rx2ELIIimMHbPGVzldCHOHIILXBxfmqm87XlhYuDAjxbbgVc/eS5Xx1ih3IawZ30pOOW2YfYwfig3BquMXM12A4XD+szNcUxwapP06Zr5rpfE3XreGWSucrIYtAAHasoB0RRvGVEEc4MkhtEAoE9AWiimEumtNcGBDi4Xw1xaWkLBBcGm7R+ZZwmPkaexQhHBpuMXYgEEJZeO5k7ABpIJwyX63NlXQ9YwfofCWkYjpaUpjNSZMIYwcI8YYjg9QIM3ZggfNVnqwFm0EQgqQ33AJk9IDDbwA5TUdLOv7/fuIBxdfYozg4X3NsuBUMp8xwe2xwjkXqj535qhU+p5YLNl2rhlvWfMqCDbcIWRR9HS0Yn83BMAzGDhDiA0cGqQ1W7EB55quWMEcfIV64OV+tBXUCxolw6HYOyNzHFjpfE44VO8DM17gisHD8F5yvHP/eOMUOcGOCNA7OztdaNdwyrw/l1w823CJkUfR3ZJDXDMzkNGQpvhLiCUcGqRFyUVDufDXshQEnPoS4O1+TM04EnPVn6XzlJSvR+Dpf4z8+4o7T/lOeZYzBcPrlacx8JY2DELJpZnHmqyXERr654pQZbhjye147CKmY/s4WAMCJmRwzXwnxgSOD1AYhoDg4Xw1NhQalqIs1IQnGNfM1Oc4+p27ngHTHMPMx4Xhl9gF098UA6Xwvvc/uhs7x741Q4O58ZewAaQxSikBeL5zDrQiCtFKj2IES8TU5VUWEREV/hym+zubs2IFWXq8JcYQrFVIbzEVBeTmhoWvQoIDTHkIAV+erJS4lYYHgkPkIADnVoPiSdJycSwBLq2OErDx2yXzl+PfBK/OVY4M0BmlFQNMKY9wSa6J3vjqIr/bGNs8thFTKQKfc3Dsxm7fCoZjRTogLHBmkZggD0MvWBdBV6PwYEiLxdb7GfwHtoL0AYOwAQWHxvMDdl5zxEXcUR+crM18DIRy6FTJ2gDQYaUWUZL5mzWu7iLoCztH5mqCNbUIioq+jKHaAMUGEeMKRQWqD1XDLIfNVE1wUECJxy3xNTuyAk34AWA23eMlKNPbi2a20Ov7jI+4IB+e7jBwR0YszTY9Xwy3GDpDGIJ1SStYCOVWvTYmyp/OV1w5CKqU4diDPzFdCPOHIIDVCQEBfkPkqdBU6QwcIkbgpj7Y7I/6nbEUIGA7u3zydr8S34RY38podIcTChlsaI0cC4VQ5oZvOV44N0iCkFAG1qAyuZtd2Ol8JiYTe9gyEkLEDbLhFiNLNhd4AACM+SURBVDccGaQ2mJMevbyekM5XQorwcL6KZDSmE8CCsmNAxg6w7Djh2JmvLu4+LqCbHjn+yzJfVTbbC4Rwynw1xaUUna+kMUgrAmpZ5mtNxreT+KrmzINqjf79CYkpKUWgtz2DEzM5ZBk7QIgnHBmkNpixAwsa6egqdC6YCZG4Zb4aWmKcS07ON4ACDLFgU6E4ozjsr8jYAY59fxw27zQ6X0ljkU6JBbEDtXW+Fo0RLStvUy3Rvz8hMaa/owUnZguZr610vhLiCEcGqRHOma9C1xg7QIiNm/NVTYyrTyYvLPwdsOEWASAX0AvEV/N7CkxNj2y4tTDztYWud38YO0CagLSilDTcqtm13dH5aoqvdL4Ssij6OzIYn80XGm5xvk6IIxwZpDYIAWEYC8qJha5CZ9A9IRI356uuJ6YhhIDzr0AKMLxkJR7H0mo23IoLQhS0dIu8ZiDDhZw/6XYgP1d6nzU2GDtAGoTyzNecatTm2m7H1ujAgXuAiUMUXwmpEgOdLRidzjLzlRAfODJIbRAK4OR8NVTozHwlpAiX2IHEOF9dGm6pBidzxL6WlMDYgdgghFjgfM8xdiAYHQPA3FjpfZo1Nii+ksZgQearptdmc0UIAEJeL758JfClK4tiByi+ErIYVvd3YP/YbMH5yms2IY5wZJAaYcYOGOXiqwYjIaISIb64Ol+1xLj6FOEoP1OAIRLH2AGKr3HBqeFennnPwWgfAHLTBTcfYMYOCEDh7480BgszXzW01mp8KylgfL/8eupwUcMtZr4Sshg2DHViNqfh0Ik5KAJI85pNiCMcGaQ2WA23ylZViq7CoPOVEBOPzNeEiK/CIfMRkAIMna/EWXw1O7onZIzEGUUs3H1h5mtAOvrl7WyR+1VXGTlAGopUeeZrLa/tQgGGH5dft/bQ+UpIlVg/1AkAePLYFOfqhHjA0UFqhFw46WWLZsXQYNCtRIjEzfmapNgBOP8KsnS+EgCAU1MhZr7GBUWBQ8Mtg2M/CO0D8rY4ekDLM3KANBTp8szXWjbTFApw7DH5dc/KoszXttq8PyExZcOgFF93Hpti5AAhHnB0kNpgdhk1DKMkz1EYKsVXQmzcnK8JarglxILfgGEYdL8RiVAWiq+G5XzltaTZEVjofGfkSEA6TPG13PnKcUEaiPLM17xqIFOra3txZriSLhJfGTtAyGJY2deGTEpgNqfR+UqIBxwdpDaYXUaL89wMw0AKycmyJMQXL+drQsaJ/BWU/g403YBhgAIMYeZrzHFIHUC+Vg15mp2OQXk7Vx47wHFBGocFma+ajpZ0jeY3oug8kp1k7AAhVSKdUrBmoAMAm20R4gVHB6kRlvhq2JMuVZfiKzNfCbHwyHxNcOyAlQ/HAH8i1TmKr3FFZj6X3kfXe0DaHZyvjB0gDUZKUZAvz3yt1bW9RHydZsMtQqrIxqEuAKDzlRAPODpIbRDWjWGXFOZUHWloXDATYuHmfNWT43xVhFjwK8hpUmyrWWkiaVyEwwaFztiBuKA47L7IsmROV33pcMh81TnHIo1FWhHQijJfszVtuFU0h8hOAeq8eVDMfCVksWxdLsVXIThXJ8QNzmZJbTB3m5Uy8TUFnSVxhNi4OF+T1HBLLGy4Y+XDUYAhnrEDgp+PZkdxcb5y7Acg0w6k28syX/OcY5GGYkHmq6ajtVbiqyX6ptvk2MhOyu8ZO0DIotm6vAcAcPDEbJ2PhJDGhbNZUiMWxg7kNB0ZOl8JKeDpfE3GOHGSn1XT+Zqm85Uw8zXWyFx4NtyqmI4BYO5E4Xstz3FBGooFma+qXruqlty0vO1ZJW9nj5sHxdgBQhbL1mXdAIC85rCOIYQAoPhKakVRCYK18SydrxoE88gIMXHLfNUAJRmna+EQO2Dlw2US8jsgXjhsUDB2IDY4jn9NR0uaGy+BaB8oc76qzHwlDUVKUewcd8BquFWra7v5vr2m+Dpjiq90vhKyaDYMddb7EAhpeLiSJTWiyPlqrqyyVuYrS+IIkVhl0+XqQ8JiBwyUxw7Q+UpMHJ2vFF/jglPsSF5j5mtgOvrLMl9VzrFIQ5FWBFTThaHpshquJVXj+Y3lfJ0ZASCAFDcoCFksbLRFiD+ckZHaUJT5ascOqDo6oUFwwUyIxHKIG0ZpY4gkxQ44GButEqY0BRjiGTuQjA2KOKM47K/kVcYOBKalu9T5ytgB0mCkFQHNvKbnzY3Vmos2duzAKJBuLZ1vEUIq5sa/ugwtvF4T4gpnZKQ2iILz1TAKk66U0CHoyiDExFoAlJdVq4kRlgSEfY6wsBZoGSdlhiQLoTjEDqjSGc4FdNMjG24x87ViMu1AvqjZCWMHSIORTgk7diCrmtf2Wle12LEDo4wcIKSKbF7aVe9DIKSh4WyW1IiFsQM5TcYOCJb7ECIpdr4WY+iJiR1QhFPDLTPzlQIMEQ65yAnanIg7QqCkGQ9gZr4yciQYmTYgP1/4XldZUk0aipRSEF9zpvjaWnPn62p5O3tcOl8JIYSQGsCVLKkNtvMVJbEDKWhQ6HwlxMTD+ZqQcSKEgL6g4RYzX4mJEM6xAyytjgUpRSkZ/5puQDe48RKYTIeD85UbE6RxSCuKneOeq1fsgOV8zU1TfCWEEFIzOJsltcHMfBXQYeooyKk6MtCg0JVBiMTWXp2cfckQlwSwIHaAzldi45T5auiJGR9xJ6MIO2YEKIocYSOPYKTbALXI+arlGTtAGoq0ImwTRl6tV+brysLXqZbavjchhJDEwtksqRFFzlejkPWUgg6R5sKAEIlX5msyxCXhGDtgOl+Z+Urg5nyluy8OpFPC3mwBCs44brwEJNMhxVdrl1vPM3aANBSposxX2/maqvH5u60P9nyLzldCCCE1grNZUhuKGm7pZZmvqYSUUxPii1vma6LE14UNt6wFWpoCDHFruJWQ8RF30ikFql7kfLWccYwcCUamTd5a7ldd49ggDUXaIfO15g23hADa+8wDovhKCCGkNnAlS2pEkfhaNOlKM3aAkCLcnK9aYpx9Mnag9L5C7MD/397dx9qW1vUB/z775dy3uTN3hhkYYEBQEaTgC50CRtMiGgRrpC+2pWqgisU2JtXGxoCkMW20tS+pbWNrQn2jDdVaSls0tZVaE9sm0qoEhwoqQUFGBoZ5n7kv5+y9n/6x1jpnn3PP5c69c/fr+nwSss/e5wxnDay1zlrf/dvfRwDTe8fVDghft0ZTO2Dy9bqNTzePexeax+meY4O1MhoMMp3V1FpzaVW1A0ly5o7mcSh8BWA5XM2yHO1E3yB1v3ZgbzLNuEwzGLkxgCQmX5MMSrk8fJ0JYGgdG75Ok9KPNye23bANZjp7E33P12R8qnmctOGr2gHWTFcfNJ3V/U7n1YSvT283SOcrAMvhapblKHOdr/tF+5MkydCFD7R0vpaS/WqSzp7JVzql5PjjQ/i6DcbDwwtu7Vpw69qM2vC1m3zt0d8ONsOw/Ts+mdX92oETKwlfb283yOQrAMvhiowlma8daF6Z7O4mSYYW3IKGydckxyy4NesW3BLA9N6VJl97dHxss9HcYjxJDibjvPHy5IyPhK/Tfv3tYP11k6/z4evSJtv/1FuT009rvu5qB3S+ArAk7mRZjnIw0ffEbjPxOpnuJUmGagegUdpT8rHhUj8m+46rHegmX0cCGCy4tdXm+yCTg/BV7cCT1C241YWvu48f9MDCGujeRH3Z331f7n242U+XVjvw1W9LXvGW5usufC2uKwBYDlezLEcbKg1S89ATzcTr3v7kq9oBSJIM2inw2eTw6z0Kl0rJfvDSEcCwrxQLbm2xrlqke8PFsX+NuqB1ciHZPZ9cejQ5+4zVbhPM6d5E3Z3Ocs+9jyRJdlZxfN/Uhq+XHlv+7wagl1zNsiQHtQMPnm9C10tt+FoGagcgSTJsA6R2Knxfj8KlUo6pHegmXwcmVCjHTL72ZzJ82w3bqbiuG37XglvXZjQ3+fr4fc3XZ5+5uu2BI4Zzf8c/8cD5JKtacKsNXy8+uvzfDUAvuZplOeYW3NqffN1rHt00Q2vYToHPehy+plxx8nUkgOHYzlcLbm2L/cnXtuf5YDV0b7w8Kd3k696F5LFPN1/fZPKV9TH/JuofPPBEkhWHryZfAVgSd7IsSXOxdebEMA+04etuF74OTb5CkoPagenu4dd7tKDQ4LjJ13YKbiUfTWS9XDF87cfxse32F+NRO3B9xsdNvt65uu2BI+YXzvzMY5cyGpTccmoF9wH74avJVwCWw90Ky9F2vt56arg/+TrZa6f73DRDo3sj4tjagZ5M9pWS2ZH0dbI/+Wr6rfdKyWXxfO3PmxPbrptu74554es1mu987Sb6bhK+sj6O/h3/gjtuyonRCq5vztzePHaL0wHAgrlbYTna2oFzp0Z58HwTLE32awfshpDkoHagz52vOW7BLZ2vtI6dfBW+bouD2oG283Wq8/WazHe+nn+g+TTF6dtWu00wZ3jk7/iLnnl2NRty4ubkFX89eek3reb3A9A77lZYkuZi69ZT43x4v/O1m3ztyUQfXM3wmNqBWnsVvh6Xr+5NZxkNSkoRvvbelWoHxqdWsz3cUPsLbnW1A5O281X4+uR0x8Hexabz9aZn7L/5Devg6CdbXnTnzavZkFKS1/3wan43AL3kapblaC/+bzk9yoOX1Q7ofIUkB+HrbHLwWhc09SR8LaVkdmTydTKrKgdo6HzdaldacGtswa0nZzhujoW988ljn0rOWmyL9dJVj3VWNvkKAEsmfGU52s7XcycPwtc9tQNw2HELbnVBbE8mxJvagcOv7U1nGQ/8uSJJyuU7yGySlH4cH9uuW4zHgltPwfh0MrnYhK/6Xlkz3T3Ay59/W249Pc6X3nVutRsEAEsi9WJJ2snXU6Nc2LuYC7vTTKfCVzjkuM7X/fC1H8fJoJTLsrXJtGY8Er6QdvL1aPiq83VbdBPuXeiq8/U6jE8lD3w0uf8jyUv/wqq3Bg5541d8Xn7304/l7/+5l+bc6Z1Vbw4ALI27FZZjbsGtJHno/G6mXe3A0G4ISeY6X/sbvqbkmNqBmcW2aJTShK3zZtPeTIZvu652YDI7PPmq8/UajE4mv/dLzdcvfv1qtwWOeNpNJ/Jj3/rHV70ZALB0rmZZqrMnmgDpkQt7mU57FirB1Ry34FYXNPXkOClJjsw1Zm9aTb7RKMfsIbM94euW2F9wq+t8nXS1A958edK6Rbfu+OLk9hesdlsAAEgifGVZ2s7Xk222dH53mpnOVzisqx2YHTf52o9waVDKZdna3nRmwS0axy24Nd07OHbYaONBVztwMPlaSjI0+f7k3f+R5vEV37na7QAAYJ/wleVoawdOtb2NTeeryVc4ZKB2oBxXOzCtagdoHBe+ziYHxw4bbTQ8vODWbjv1Xorj/0m76+XN48veuNrtAABgXz/u5lkDzY3TyVEzvffQ+d0M06+PU8NV6XzNMYOv2ZvO1A7QuOLkq/B1G+wvuNXVDkxn+l6v1Zve2yxK15NPSwAAbIJ+3M2zet3k607z+ND53YyFr3DYsZ2v/QpfB6Ucs+BWVTtAqzTB0rzprvB1S4wHhydfmzdeHPvXpOt8BQBgbRgnYDm6ztdRcxP1wOMmX+EyXW/locnXdsqvJ8fJoJTMZofDNZOv7FM7sNW6btfp3OSrYx8AgE3nipYlaWsH2puoB5/YzSjtDbSJJWh0x0KPF9waD8v+YjudvelsfyKOnlM7sNW6KdfuHLA7qcJXAAA2nitalqOtHTg5PghfDyZf+xEqwVUN1A6MBoNMZofDtclU7QCtMlA7sMX2F9ya73wduVQFAGCzuaJlSZrgZDxIRoPSTL4WtQNwyH7twOTgtb6Fr8Oy3/fY2ZvV/VCGnislh5Zkm02b52oHtsJocHjyVecrAADbwN0sy9F2vqbOcnpn2NYOCF/hkG4K/NDka7+Ok53hILvTo5Ovs4wHAhjShK/ztQNdP7LJ163QVQwcXnDLpSoAAJvNFS3LUbrgpOb0zigPPLGbYdf5amIJGqU006897nw9bvJV7QD7jna+dm9UCF+3wtEFt3anOl8BANh8rmhZkjY4qcnpnWEeOr+bcfoVKsGTMhgfTPMlPawduLzzdW82UztAqxzufO2Oj66yg412dMGtvcksO459AAA2nCtalmNu8vXUzjDTWZ2bfO1HqARPynDc6wW3xoOyH7x09qYCGFqXTb62b1T05PjYdsctuDUemXoHAGCzuZtlObrwtdac2Wlukvc7X31cFA4Md3o9+ToeDrJ3Wedr3V+Ih55TO7DVjl9wy6UqAACbzRUtS9KFr7Oc2mlqBky+wjGGR2sHugW3+lHPMRoOLut83ZtWtQM0joavXT+y2oGtcHTBLZ2vAABsA1e0LMehBbeaEOmW8aS5kRa+woHh+AoLbvXjOBkPS/aOdL5OZrP9Lkh6rpQkc+H8tF/Hx7brBtync7UDKkcAANh0rmhZkoPagW7y9c4Te8nO2blgFmgW3Opv5+toMEityXR2ELA1tQP+XBG1A1uulNK+AdMc/5cm0+yMHPsAAGw2V7QsxzGTr7fv7CYnblrdNsE66nvn66jrfDwI2HanJl9plUFS5yZf1Q5sndFgkEl7/D96YZJbTgnWAQDYbMJXlqO0u1qd5dS4CV9vG+0mO8JXOOSKna89CV/bCdcufK21ZncyywnTbyRJyuHwdb92QEC3LUbDkr1pzXRW8+jFPeErAAAbz90sy9FNJZ1/IE/sNmHS2cHF5MTZFW4UrKHhlWoH+rLgVjPhOtlf7bx59NFjkjSfopheOnhTYr92oB9vTvTBeDjIZDbLYxf3Umty7rTwFQCAzeZuluV41suSm5+dvP8defDR83lh+URO1wtqB+Co4U4TKE0uNc97VjswahfX6Rbd2m0nYIWvJEme9eXJE/cnP/fGZgJW7cDWGQ5KprOah883/98KXwEA2HTuZlmO0U7yFd+VfPx/5c8/+s78l5235abzf6h2AI4ajJKP/+/kB5/ehkv9Cl/Hg8OTr7uTNny14jlJ8ifenLz6bycf+YXknn+fTNrJV7UDW2M8aGoHHr7Qhq+nBOsAAGy2ftzNsx6e88okyVeP7smw1AwvPqB2AI6an+B7+OP9C1+Hhztf98PXUT9qF3gSvvJ7kg+9J3nPX01OnmteGwpft8VoOMilySwPPN5M/99i8hUAgA1nlIjlOXtnkmR0/4cPXjP5CofNh0j33TO34FY/wseu83Xv6OSr2gE6w1Hypp9P7vyS5OLD7WsCum0xGpb8/Af/KG9+568nSc5ZcAsAgA3nbpbluenpScpBR19i8hWOOhS+fqi3k6+TtvP10qQJn4WvHHLmacm55x48VzuwNcaDw8f6udNqBwAA2GzuZlme4Tg5c8fh1yy4BYfN1w7cd0/vwtfRkc7XS+3k6wnhK0ftnDn42uTr1ugW2evcfLIf5z4AALaXu1mWq60e2Ldj8hUOmQ9ZP92/8HXchqxdANM9mnzlMuNTB18LX7fGvQ9dOPR8ZLE9AAA2nCtaluvsMw8/N/kKh116rHkcjJPH7z/ofC396HztPnI8OdL5ekIAw1HjuclXtQNb4+jkKwAAbDp3syzXzUfDV5OvcMjFR5rHO16YTC4ku48nZZAM+nG67hbcmnSTrxbc4kpMvgIAABvA3SzLdXTydcfkKxxy4aHm8fYvah7PP9CbyoEkGbfh697s8OSr8JXL7Jw++Fr4CgAArKn+3NGzHrrO15vvSh79pMlXOOrCw83jHS9sHp+4v2fha1c7oPOVqxjPha9qB7bGN7/iubn3oQv5qi+8Pbef3bn6PwAAAGuuP3f0rIcvel3yio80H63+4L81+QpHXXy4eewmX3sWvo7aeoW9NnS9NGk6b3d0vnKU2oGt9Pf+7EtXvQkAAHBDuZtluc4+I3ndDx9MwFpwCw57zQ82Cwnd+rzm+ROfTQb9WGwrmasdOLrg1rg//xvwJB1acMv+AQAArCfhK6tx6/OS0ank1K2r3hJYL3d/W/L2P0pO39Y8f+Kz/Zp87WoHZkcW3DL5ylHzk68AAABrqj939KyXL/vm5AteneycufrPQh91b0xMLiSnzq10U5bp6OTrJQtucSXzC24BAACsKXezrMZwnJx7zqq3AtbXztmktKfoHk2+dgtu7R1ZcOuE8JWjxsJXAABg/bmbBVhHg0Fy8lz7dX/6LEeDZvJ1cqTzVe0AlxG+AgAAG8DdLMC66qoHejT5Ojo6+TqZZTQoGbShLOwTvgIAABtA+AqwrnoYvnadr5PZQeervleOZcEtAABgA7ijBVhXJ842j70KX9vJ18nB5KvwlWNZcAsAANgA7mgB1tXTvrB5/PxXrXQzlqnrfN2bHXS+WmyLY6kdAAAANkB/xqkANs1rfjB51VuTM7evekuWppSS0aBk0nW+Tk2+cgXDnVVvAQAAwFUJXwHW1fhk85+eGQ3Lfufr7mSWnaHwlWMUi7ABAADr74bc0ZZSvreUUksp/RnPAmAhxsNBdtvO12bBreGKtwgAAACuz1MOX0spz0nymiSfeOqbA0DfjYeDTGZqBwAAANh8N+KO9keSfF+SegP+uwDouabztfmTcmlvmhNqBwAAANhQT6nztZTy+iT31lo/WK7SvVZKeUuStyTJc5/73KfyawHYYuPhIHtt+Lo7neXMjnpyruDl35mcuWPVWwEAAHBFV72jLaX89yR3HvOttyf5/jSVA1dVa31Hknckyd13321KFoBjjYfloHZgMsttp02+cgVf/w9XvQUAAACf01XD11rr1x73einlpUmen6Sber0ryW+WUl5ea73vhm4lAL0xGg6yNz0IX3W+AgAAsKmu+7OctdZ7kjy9e15K+YMkd9daP3sDtguAnhoNyqHaAeErAAAAm8odLQBr5dELe3nfb386/+pXP9ZMvlpwCwAAgA11w+5oa63PM/UKwFN165mdJMl7PnBvLqkdAAAAYIO5owVgrfzoN78sz7ntVE6OB3n84iRnT45XvUkAAABwXYSvAKyV599+Ji951i357OOXsjud5ezJ664nBwAAgJUSvgKwds6eHOW+Ry4mSW4+ZfIVAACAzSR8BWDtnD05zt60JkluNvkKAADAhhK+ArB25qsGbtb5CgAAwIYSvgKwduYX2dL5CgAAwKYSvgKwdg5Nvup8BQAAYEMJXwFYO2dPHISvJl8BAADYVMJXANbOfO2AzlcAAAA2lfAVgLXTTbsOByWnd4Yr3hoAAAC4PsJXANZOF76ePTlKKWXFWwMAAADXR/gKwNrpagf0vQIAALDJhK8ArJ0udNX3CgAAwCYTvgKwdk6MBhkPi8lXAAAANprwFYC1U0rJ2ZNjk68AAABsNOErAGvpi595Ni+68+yqNwMAAACum89zArCW3vUdr1z1JgAAAMBTYvIVAAAAAGABhK8AAAAAAAsgfAUAAAAAWADhKwAAAADAAghfAQAAAAAWQPgKAAAAALAAwlcAAAAAgAUQvgIAAAAALIDwFQAAAABgAYSvAAAAAAALIHwFAAAAAFgA4SsAAAAAwAIIXwEAAAAAFkD4CgAAAACwAMJXAAAAAIAFEL4CAAAAACyA8BUAAAAAYAGErwAAAAAACyB8BQAAAABYAOErAAAAAMACCF8BAAAAABZA+AoAAAAAsADCVwAAAACABRC+AgAAAAAsgPAVAAAAAGABhK8AAAAAAAsgfAUAAAAAWADhKwAAAADAAghfAQAAAAAWQPgKAAAAALAAwlcAAAAAgAUQvgIAAAAALIDwFQAAAABgAYSvAAAAAAALIHwFAAAAAFgA4SsAAAAAwAIIXwEAAAAAFkD4CgAAAACwAMJXAAAAAIAFEL4CAAAAACyA8BUAAAAAYAGErwAAAAAACyB8BQAAAABYgFJrXf4vLeX+JB9f+i9erduTfHbVGwFLZr+nr+z79JH9nj6y39NX9n36yH7P5/J5tdY7jvvGSsLXPiql/Hqt9e5Vbwcsk/2evrLv00f2e/rIfk9f2ffpI/s910vtAAAAAADAAghfAQAAAAAWQPi6PO9Y9QbACtjv6Sv7Pn1kv6eP7Pf0lX2fPrLfc110vgIAAAAALIDJVwAAAACABRC+AgAAAAAsgPB1wUopry2l/E4p5aOllLeuenvgRiqlPKeU8iullN8upfy/Usp3t6/fVkp5Xynl99rHW9vXSynln7fHw2+VUl622n8DuH6llGEp5QOllF9onz+/lPL+dv/+d6WUnfb1E+3zj7bff95KNxyuUynlXCnl3aWUj5RSPlxK+Qrne/qglPI32+ucD5VSfqaUctI5n21TSvnJUspnSikfmnvtms/xpZQ3tT//e6WUN63i3wWuxRX2/X/UXu/8VinlP5ZSzs19723tvv87pZSvm3td9sMVCV8XqJQyTPIvkrwuyYuT/OVSyotXu1VwQ02SfG+t9cVJXpnku9p9/K1JfrnW+oIkv9w+T5pj4QXtf96S5MeWv8lww3x3kg/PPf8HSX6k1vqFSR5K8ub29Tcneah9/Ufan4NN9M+S/Nda64uSfGma/d/5nq1WSnl2kr+R5O5a60uSDJO8Ic75bJ+fTvLaI69d0zm+lHJbkh9I8ookL0/yA11gC2vsp3P5vv++JC+ptX5Jkt9N8rYkae9135Dkj7X/zL9sBzJkP3xOwtfFenmSj9ZaP1Zr3U3ys0lev+Jtghum1vqpWutvtl8/luZG/Nlp9vN3tj/2ziR/pv369Un+dW38WpJzpZRnLner4akrpdyV5E8n+fH2eUny6iTvbn/k6H7fHQ/vTvI17c/Dxiil3JLkTyb5iSSpte7WWh+O8z39MEpyqpQySnI6yafinM+WqbX+apIHj7x8ref4r0vyvlrrg7XWh9IEWEdDLVgrx+37tdZfqrVO2qe/luSu9uvXJ/nZWuulWuvvJ/lomtxH9sPnJHxdrGcn+cO5559sX4Ot036s7suTvD/JM2qtn2q/dV+SZ7RfOybYFv80yfclmbXPn5bk4bmLtPl9e3+/b7//SPvzsEmen+T+JD/V1m38eCnlTJzv2XK11nuT/OMkn0gTuj6S5DfinE8/XOs53rmfbfTtSX6x/dq+z3URvgJPWSnlpiT/Icn31Fofnf9erbUmqSvZMFiAUso3JPlMrfU3Vr0tsESjJC9L8mO11i9P8kQOPn6axPme7dR+ZPr1ad6AeFaSMzHJRw85x9NHpZS3p6nae9eqt4XNJnxdrHuTPGfu+V3ta7A1SinjNMHru2qt72lf/nT38dL28TPt644JtsFXJvnGUsofpPlI0avTdGGeaz+Smhzet/f3+/b7tyR5YJkbDDfAJ5N8stb6/vb5u9OEsc73bLuvTfL7tdb7a617Sd6T5u+Acz59cK3neOd+tkYp5a8k+YYk39K++ZDY97lOwtfF+r9JXtCuhrqTppj5vSveJrhh2g6zn0jy4VrrP5n71nuTdKubvinJf557/Y3tCqmvTPLI3EeZYCPUWt9Wa72r1vq8NOf1/1Fr/ZYkv5Lkm9ofO7rfd8fDN7U/b3KEjVJrvS/JH5ZSXti+9DVJfjvO92y/TyR5ZSnldHvd0+37zvn0wbWe4/9bkteUUm5tp8Zf074GG6WU8to0FWPfWGs9P/et9yZ5QynlRCnl+WkWnfs/kf1wFcW1wGKVUr4+TTfgMMlP1lp/aLVbBDdOKeWrkvzPJPfkoPvy+9P0vv5ckucm+XiSv1hrfbC9afnRNB/XO5/k22qtv770DYcbpJTyqiR/q9b6DaWUz08zCXtbkg8k+dZa66VSyskk/yZNJ/KDSd5Qa/3YijYZrlsp5cvSLDK3k+RjSb4tzRv5zvdstVLK30nyl9J89PQDSb4jTZefcz5bo5TyM0leleT2JJ9O8gNJ/lOu8RxfSvn2NPcDSfJDtdafWuK/BlyzK+z7b0tyIgefXPi1Wutfa3/+7Wl6YCdpavd+sX1d9sMVCV8BAAAAABZA7QAAAAAAwAIIXwEAAAAAFkD4CgAAAACwAMJXAAAAAIAFEL4CAAAAACyA8BUAAAAAYAGErwAAAAAAC/D/Adq2MhBV957sAAAAAElFTkSuQmCC\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"code","source":"###### Creating Numpy Arrays\nnp.savez_compressed('X_train_va_cd_emp.npz',np.array(X_train_va))\nnp.savez_compressed('y_va_cd_emp.npz',np.array(y_va))\nnp.savez_compressed('X_dev_va_cd_emp.npz',np.array(X_dev_va))\n\n##### Loading Dataset\nX_train_va = np.array(np.load('./X_train_va_cd_emp.npz',allow_pickle=True)['arr_0'],dtype=np.float16)\nX_dev_va = np.array(np.load('./X_dev_va_cd_emp.npz',allow_pickle=True)['arr_0'],dtype=np.float16)\ny_va = np.load('./y_va_cd_emp.npz',allow_pickle=True)['arr_0']\n\n##### Converting Labels to Categorical Format\ny_va_ohot = tf.keras.utils.to_categorical(y_va)","metadata":{"execution":{"iopub.status.busy":"2021-09-08T19:11:20.412463Z","iopub.execute_input":"2021-09-08T19:11:20.412995Z","iopub.status.idle":"2021-09-08T19:11:20.456934Z","shell.execute_reply.started":"2021-09-08T19:11:20.412963Z","shell.execute_reply":"2021-09-08T19:11:20.456118Z"},"trusted":true},"execution_count":83,"outputs":[]},{"cell_type":"code","source":"###### Extracting Embeddings\nwith tpu_strategy.scope():     \n\n    def normalisation_layer(x):   \n        return(tf.math.l2_normalize(x, axis=1, epsilon=1e-12))\n\n    #X_dev_flipped = tf.image.flip_up_down(X_dev)  \n    #x_train_flipped = tf.image.flip_up_down(X_train_final)\n\n    predictive_model = tf.keras.models.Model(inputs=model.input,outputs=model.layers[-3].output)\n    predictive_model.compile(tf.keras.optimizers.Adam(lr=1e-4),loss='categorical_crossentropy',metrics=['accuracy'])\n\nwith tpu_strategy.scope():\n    y_in = tf.keras.layers.Input((20,))\n\n    Input_Layer = tf.keras.layers.Input((1280,1))\n    op_1 = predictive_model([Input_Layer,y_in])\n\n    ##Input_Layer_Flipped = tf.keras.layers.Input((224,224,3))\n    ##op_2 = predictive_model([Input_Layer_Flipped,y_in]) \n    ##final_op = tf.keras.layers.Concatenate(axis=1)(op_1)\n\n    final_norm_op = tf.keras.layers.Lambda(normalisation_layer)(op_1)\n\n    testing_model = tf.keras.models.Model(inputs=[Input_Layer,y_in],outputs=final_norm_op)\n    testing_model.compile(tf.keras.optimizers.Adam(lr=1e-4),loss='categorical_crossentropy',metrics=['accuracy'])\n\n##### Nearest Neighbor Classification\nfrom sklearn.neighbors import KNeighborsClassifier\nTest_Embeddings = testing_model.predict((X_dev_va,y_va_ohot)) # Session-2 Embeddings\nTrain_Embeddings = testing_model.predict((X_train_va,y_va_ohot)) # Session-1 Embeddings\n\ncol_mean = np.nanmean(Test_Embeddings, axis=0)\ninds = np.where(np.isnan(Test_Embeddings))\n#print(inds)\nTest_Embeddings[inds] = np.take(col_mean, inds[1])\n\ncol_mean = np.nanmean(Train_Embeddings, axis=0)\ninds = np.where(np.isnan(Train_Embeddings))\n#print(inds)\nTrain_Embeddings[inds] = np.take(col_mean, inds[1])","metadata":{"execution":{"iopub.status.busy":"2021-09-08T19:11:23.140491Z","iopub.execute_input":"2021-09-08T19:11:23.141009Z","iopub.status.idle":"2021-09-08T19:11:32.874310Z","shell.execute_reply.started":"2021-09-08T19:11:23.140974Z","shell.execute_reply":"2021-09-08T19:11:32.873231Z"},"trusted":true},"execution_count":84,"outputs":[]},{"cell_type":"code","source":"###### Full Embedding Creation\nEmbeddings = np.array(list(Test_Embeddings)+list(Train_Embeddings))\ny_va_full = np.array(list(y_va)+list(y_va+20))\nprint(y_va_full)","metadata":{"execution":{"iopub.status.busy":"2021-09-08T19:11:32.875820Z","iopub.execute_input":"2021-09-08T19:11:32.876146Z","iopub.status.idle":"2021-09-08T19:11:32.883356Z","shell.execute_reply.started":"2021-09-08T19:11:32.876116Z","shell.execute_reply":"2021-09-08T19:11:32.882359Z"},"trusted":true},"execution_count":85,"outputs":[{"name":"stdout","text":"[ 0  0  0  0  0  1  1  1  1  1  2  2  2  2  2  3  3  3  3  3  4  4  4  4\n  4  5  5  5  5  5  6  6  6  6  6  7  7  7  7  7  8  8  8  8  8  9  9  9\n  9  9 10 10 10 10 10 11 11 11 11 11 12 12 12 12 12 13 13 13 13 13 14 14\n 14 14 14 15 15 15 15 15 16 16 16 16 16 17 17 17 17 17 18 18 18 18 18 19\n 19 19 19 19 20 20 20 20 20 21 21 21 21 21 22 22 22 22 22 23 23 23 23 23\n 24 24 24 24 24 25 25 25 25 25 26 26 26 26 26 27 27 27 27 27 28 28 28 28\n 28 29 29 29 29 29 30 30 30 30 30 31 31 31 31 31 32 32 32 32 32 33 33 33\n 33 33 34 34 34 34 34 35 35 35 35 35 36 36 36 36 36 37 37 37 37 37 38 38\n 38 38 38 39 39 39 39 39]\n","output_type":"stream"}]},{"cell_type":"code","source":"###### t-SNE Plotting \n\n##### Testing Dataset - Session 2\n#### Reduction to Lower Dimensions\ntsne_X_dev_va = TSNE(n_components=2,perplexity=30,learning_rate=10,n_iter=2000,n_iter_without_progress=50).fit_transform(Embeddings)\n\n#### Plotting\nj = 0 # Index for rotating legend\nplt.rcParams[\"figure.figsize\"] = [24,18]\nmStyles = ['o','o','o','o','o','o','o','o','o','o','o','o','o','o','o','o','o','o','o','o',\n           's','s','s','s','s','s','s','s','s','s','s','s','s','s','s','s','s','s','s','s'] # Sqaure Session 1 data while Circle Session 2\nfor idx,color_index,marker_type in zip(list(np.arange(40)),list(sns.color_palette('muted',20)+sns.color_palette('muted',20)),mStyles):\n    plt.scatter(tsne_X_dev_va[y_va_full == idx, 0], tsne_X_dev_va[y_va_full == idx, 1],marker=marker_type,color=color_index,linewidths=3)\nplt.legend([str(j) for j in range(20)])\nplt.legend([str(j-20) for j in range(20,40)])\nplt.show()","metadata":{"execution":{"iopub.status.busy":"2021-09-08T19:11:33.311137Z","iopub.execute_input":"2021-09-08T19:11:33.311530Z","iopub.status.idle":"2021-09-08T19:11:35.233065Z","shell.execute_reply.started":"2021-09-08T19:11:33.311482Z","shell.execute_reply":"2021-09-08T19:11:35.232147Z"},"trusted":true},"execution_count":86,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1728x1296 with 1 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]}]}